on developing quadrature spatial modulation for space ... · a thesis submitted in partial...
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On Developing Quadrature Spatial Modulation
for Space -Time Block Coding and for Wireless
Relaying Networks
شبكات ول الكتمي زمكانيالترميز ال ألنظمة متعامد توليف مكاني رنحو تطوي
االتصاالت الالسمكية التعاونية
By
Mohammed Soud Mohareb
Supervised by
Dr. Mohammed Taha O. El Astal
Assistant Prof. of Electrical
Engineering
Dr. Ammar M. Abu Hudrouss
Associate Prof. of Electrical
Engineering
A thesis submitted in partial fulfillment
of the requirements for the degree of
Master of Engineering in Electrical Engineering
December/2017
زةــغ – تــالميــــــت اإلســـــــــامعـالج
البحث العلمي والذراساث العليا عمادة
الهنذســـــــــــتت ليــــــك
الهنذست الكهربائيت ماجستير
The Islamic University– Gaza
Deanship Research and Graduate Studies
Faculty of Engineering
Master of Electrical Engineering
I
إقــــــــــــــرار
العنوان:أنا الموقع أدناه مقدم الرسالة التي تحمل
On Developing Quadrature Spatial Modulation for
Space -Time Block Coding and for Wireless
Relaying Networks
شبكاتول الكتمي زمكانيالترميز ال ألنظمة متعامد توليف مكاني نحو تطوير االتصاالت الالسمكية التعاونية
ىو نتاج جيدي الخاص، باستثناء ما تمت اإلشارة إليو حيثما ورد، أقر بأن ما اشتممت عميو ىذه الرسالة إنما
لنيل درجة أو لقب عممي أو بحثي لدى أي خريناآل وأن ىذه الرسالة ككل أو أي جزء منيا لم يقدم من قبل
مؤسسة تعميمية أو بحثية أخرى.
Declaration
I understand the nature of plagiarism, and I am aware of the University‟s policy on
this.
The work provided in this thesis, unless otherwise referenced, is the researcher's own
work, and has not been submitted by others elsewhere for any other degree or
qualification.
:Student's name محمذ سعىد محارب اسم الطالب:
:Signature محمذ محارب التوقيع:
6/12/2017 التاريخ:Date:
II
Abstract
Multiple input multiple output (MIMO) techniques are one of the most
important technologies in the 4th
generation wireless systems, and will have a key
role in meeting the requirements of 5G.
Wireless relaying networks (WRNs) have been emerged to avoid the
limitations of MIMO by its potential that attains the performance gains of multiple-
input multiple-output (MIMO) in networks containing single antenna terminals. In
addition, it can be combined with Space time block codes (STBC), termed as D-
STBC, to improve the achieved reliability and spectral efficiency.
Recently, a promising transmission scheme called spatial modulation (SM) has
been proposed to provide several advantages over conventional MIMO as: Higher
throughput, simpler receiver/transmitter design, and better spectral/ energy
efficiency. Recently, SM has seen further development to yield Quadrature spatial
modulation (QSM) which is has a great potential to increase the spectral efficiency
and to offer better performance (BER), while preserving the decoding complexity to
the same level. The existing research efforts in either Space-Time-Block-Coded and
distributed Quadrature Spatial Modulation are limited. This thesis proposes a STBC-
QSM coding technique that is basically dependent on Alamouti‟s STBC code but can
be easily extended to other STBC codes. Unlike QSM, a transmit diversity of 2nd
order or higher can be obtained. Both diversity and complexity of the proposed
design is analysed and compared to state-of-art schemes. Simulation results, which
corroborate the theoretical ones, show the effectiveness of STBC-QSM scheme
proposed in improving the overall performance and the spectral efficiency. Moreover
a brief explanation for the basis of QSM-STBC in WRNs is introduced.
In addition, this thesis introduces a transmission protocol that adapts QSM into
wireless relaying networks, in order to obtain better spectral efficiency and reliability
compared to the state-of-art WRN transmission protocols. In addition, it is analysed
theoretically to corporate the included numerically simulation. It is shown that the
performance and gain of the proposed protocol and scheme outperform the state-of-
art WRN transmission protocols.
III
الملخص
من أىم تقنيات الجيل الرابع MIMO)تعتبر تقنيات االتصاالت متعددة المداخل والمخارج ) الالسمكية ، كما أنو سيكون ليا دور أساسي في تحقيق متطمبات الجيل الخامس. لالتصاالت
الموجودة في تقنيات المعوقات حتى تتغمب عمىأت نش WRNs)شبكات االتصاالت التعاونية )جعل األنظمة وحيدة المدخل والمخرج أن وذلك يرجع إلى قدرتيا عمى، االتصاالت متعددة المداخل والمخارج
بحيث يتم (Virtual MIMOمخارج افتراضي )ن نظام متعدد المداخل والن مع بعضيا البعض لتكو تتعاو لى أنو يمكن دمج شبكات إ، باإلضافة داء تقنيات االتصاالت متعددة المداخل والمخارجأتحقيق نفس
نظام اسم الوفي ىذه الحالة يطمق عمى ، (STBC)االتصاالت التعاونية مع نظام الترميز الزمكاني الكتمي ىذا النظام لتحسين الموثوقية وزيادة كفاءة الطيف . وييدف(. D-STBCز ع )الترميز الزمكاني الكتمي المو
( ، ويحقق التوليف Spatial Modulationرسال واعد يسمى التوليف المكاني )إ، تم اقتراح نظام مؤخرا معدل إرسال صحيح( أبرزىا ) تحقيق MIMOت متعددة المداخل والمخارج )المكاني عدة مميزات عمى التقنيا
(throughput أعمى )– تم أفضل في كفاءة طاقة الطيف(. حديثا –أبسط في تصميم المرسل والمستقبل ،حيث أن ىذا ، (QSM)المتعامدتطوير نظام التوليف المكاني لينتج نظام جديد يعرف باسم التوليف المكاني
النظام يمتمك القدرة عمى زيادة كفاءة الطيف ويؤدي إلى تحسين كفاءة البث، مع المحافظة عمى مستوى التعقيد متعامد المكاني ال في مجال التوليف في نظام فك التشفير كما ىو في حالة التوليف المكاني. الجيود البحثية
ىذا .ىي جيود محدودة التصاالت الالسمكية التعاونيةكتمي ومع شبكات االزمكاني الترميز المدمج مع ال ووى STBC-QSM)المتعامد )البحث يقترح نظام ارسال باستخدام الترميز الزمكاني الكتمي والتوليف المكاني
بسيولة ألنظمة ترميز زمكاني كتمي و، ولكن يمكن توسعتAlamoutiعتمد عمى االرسال باستخدام ترميز يذات درجات أعمى. تم تحميل التباعد والتعقيد لمنظام المقترح، وتم مقارنتو مع أنظمة أخرى، حيث أثبتت النتائج
كما تم .الرقمية التي دع مت التحميل النظري فاعمية النظام المقترح في تحسين األداء العام وكفاءة الطيفعمى شبكات االتصاالت الالسمكية STBC-QSM)يف الخوارزمية المقترحة)لتكي تناول شرح مختصر
التعاونية.كما أن البحث اقترح بروتوكوال جديدا يقوم بتكييف نظام التوليف المكاني المتعامد عمى شبكات
لشبكات االتصاالت الالسمكية التعاونية لتحقيق كفاءة طيف وموثوقية عالية بالمقارنة بالبروتوكوالت األخرى وتم التحقق من ذلك من خالل التحميل النظري والنتائج الرقمية التي أثبتت أن ،االتصاالت المالسمكية التعاونية
أداء وكسب البروتوكول المقترح تتفوق عمى البروتوكوالت األخرى لشبكات االتصاالت المالسمكية التعاونية.
IV
Potential publications
[1] M. Muhareb, A. M. Abu-Hudrouss, and M.-T O. El Astal, “Quadrature
spatial modulation for wireless relaying networks,” The IEEE International
Conference on Innovative Trends in Computer Engineering (ITCE 2018),
Accepted, Nov. 2017.
[2] M. Muhareb, M.-T O. El Astal, and A. M. Abu-Hudrouss, “Space-time
block coded quadrature spatial modulation,” IET Electronics Letters,
revised draft submitted, Nov. 2017.
V
Dedication
All praises go to Allah, the Lord of mankind, the King of mankind, and the Ilah
(God) of mankind
To the soul of my beloved mother
Who gave me the most precious things she has. I ask Allah to give her the reward,
according to the best rewards that given to the mother due to her son.
To my beloved father
Who encouraged me and has given me endless support during the work of this thesis.
To my dear brothers and sisters
For their continued support
To my great family
To my special friends
To my country, Palestine
VI
Acknowledgment
Foremost, based on trust and good thinking in ALLAH, and with facilitations
of ALLAH; this work has been accomplished successfully.
My gratitude directs to my supervisors Dr. Mohammed Taha O. El Astal and
Dr. Ammar M. Abu-Hudrouss for their encouragement, valuable advices, patience,
motivation, enthusiasm, and immense scientific efficiency.
Furthermore, I would like to thank, my examiners, Dr. Talal Skaik and Dr.
Yousef Hamouda for their efforts in reviewing my thesis, and insightful comments.
Also, my sincere thanks go to all my teachers through the journey of a Master
degree.
I like also to thank my special friends and colleagues of work for their help
and continues support.
I would exploit this opportunity, to kiss my mother's feet. That is a great
mother who taught me how the letters can be written, and how the numbers can be
added. She planted in me everything that is beautiful of values and ethics, and taught
me the value of the study. I was hoping she witnesses this moment, but she departed
us before a few months. I donate this thesis for her pure soul, and I ask ALLAH to
make this work in her advantages.
I would mostly like to thank my great father for his limitless support, guidance
and motivation. I am also grateful to my brothers and sisters for their wonderful help.
Last but not least, all thanks to anyone who prayed for me.
Mohammed S. Muhareb
December, 2017
VII
Table of Contents
Declaration .................................................................................................................... I
Abstract ........................................................................................................................ II
Abstract in Arabic ...................................................................................................... III
Potential publications ................................................................................................. IV
Dedication .................................................................................................................... V
Acknowledgment ....................................................................................................... VI
Table of Contents ...................................................................................................... VII
List of Tables ............................................................................................................. IX
List of Figures .............................................................................................................. X
List of Abbreviations ................................................................................................. XI
Chapter 1 Introduction ............................................................................................. 1
1.1 Introduction ........................................................................................................ 2
1.2 Motivation: ......................................................................................................... 2
1.3 Problem Statement ............................................................................................. 3
1.4 Research Objectives ........................................................................................... 3
1.5 Literature review ................................................................................................ 4
1.6 Thesis contributions ........................................................................................... 7
1.7 Thesis organization ............................................................................................ 7
Chapter 2 Thesis’s Background (WRNs, STBC, and SM) ................................... 9
2.1 Introduction ...................................................................................................... 10
2.2 MIMO Communication System....................................................................... 10
2.2.1 MIMO Channel Model ............................................................................. 12
2.3 Cooperative Communication ........................................................................... 13
2.3.1 Common Relaying Protocols .................................................................... 15
2.3.1.1 Fixed relaying protocols .................................................................... 17
2.3.1.2 Adaptive relaying protocols .............................................................. 20
2.3.1.3 Comparison between different relaying protocols ............................. 22
2.4 Space -time code (STC) ................................................................................... 23
2.4.1 Alamouti Space –Time Code .................................................................... 24
2.4.1.1 Alamouti Encoding ............................................................................ 24
2.4.1.2 Alamouti Decoding ............................................................................ 26
2.4.1.3 Simulation result ............................................................................... 28
2.4.2 Space Time Block Coding ........................................................................ 28
2.4.3 Distributed Space Time Block Coding ..................................................... 29
2.4.3.1 D-STBC definition ............................................................................. 29
2.4.3.2 D-STBC with using Alamouti ........................................................... 30
2.4.3.3 General D-STBC ............................................................................... 31
2.5 Spatial Modulation (SM) ................................................................................. 32
2.5.1 SM transmitter .......................................................................................... 33
2.5.2 SM receiver ............................................................................................... 34
VIII
2.6 Conclusion ....................................................................................................... 35
Chapter 3 Space-Time Block Coded Quadrature Spatial Modulation ............... 36
3.1 Introduction ...................................................................................................... 37
3.2 Quadrature spatial modulation (QSM) ............................................................ 38
3.2.1 QSM transmitter ....................................................................................... 39
3.2.2 QSM receiver ............................................................................................ 41
3.2.3 Comparison between SM and QSM performance .................................... 41
3.3 System model ................................................................................................... 42
3.4 The proposed STBC-QSM coding scheme ...................................................... 44
3.5 Performance Analysis ...................................................................................... 47
3.5.1 Diversity Analysis ..................................................................................... 47
3.5.2 Complexity Analysis................................................................................. 47
3.5.3 Efficiency Analysis ................................................................................... 48
3.6 Simulation results ............................................................................................ 48
3.7 Distributed Space – Time Block Code Quadrature Spatial Modulation (D-
STBC-QSM) .......................................................................................................... 51
3.8 Conclusion ....................................................................................................... 52
Chapter 4 Quadrature Spatial Modulation for Wireless Relaying Networks ... 53
4.1 Introduction ...................................................................................................... 54
4.2 System model ................................................................................................... 55
4.3 The proposed transmission protocol ................................................................ 56
4.4 Diversity analysis ............................................................................................. 60
4.5 Simulation results ............................................................................................ 61
4.6 Conclusion ....................................................................................................... 64
Chapter 5 Conclusion and Future Works ............................................................. 65
5.1 Conclusion ....................................................................................................... 66
5.2 Future Works.................................................................................................... 67
The Reference List ................................................................................................... 69
IX
List of Tables
Table (2.1) : Alamouti encoding process. ................................................................. 25
Table (2.2) : Alamouti channel parameters. .............................................................. 26
Table (2.3): SM mapping for 4bit/s/Hz ..................................................................... 34
Table (3.1) : QSM mapping for 4bit/s/Hz ................................................................. 40
Table(3.2): The mapping table for a code in example 3.1. ....................................... 45
Table (3.3): The -mapping table for a code in example3.2. ...................................... 46
Table(3.4): The mapping table for a code in example3.3. ........................................ 46
Table(3.5): Comparison of spectral efficiency for different systems. ...................... 48
Table(4.1): The code-mapping table for example 4.1. .............................................. 59
Table(4.2): The code-mapping table for example 4.2. .............................................. 60
X
List of Figures
Figure (2.1): Multiple - antenna system types. ......................................................... 11
Figure (2.2): Block diagram of a MIMO system using spatial multiplexing. .......... 12
Figure (2.3): MIMO communication scheme. .......................................................... 13
Figure (2.4): Hardware constraint of MIMO. ........................................................... 13
Figure (2.5): A simplified cooperation model. ......................................................... 14
Figure (2.6): Phases of relaying network. ................................................................ 15
Figure (2.7): Relaying system model. ...................................................................... 16
Figure (2.8): Amplify and Forward (AF) relaying protocol. .................................... 17
Figure (2.9): Decode and Forward (DF) relaying protocol. .................................... 18
Figure (2.10): Compress and Forward relaying protocol. ........................................ 19
Figure (2.11): Coded relaying protocol. .................................................................. 19
Figure (2.12): Selective Amplify and Forward (SAF) relaying protocol . .............. 21
Figure (2.13): The SER performance of DF, AF, and SDF relaying protocols.. ...... 22
Figure (2.14): Outage probability versus spectral efficiency for DF, AF, SDF and
incremental relaying protocols. .......................................................................... 23
Figure (2.15): Illustration of STBC transmission. .................................................... 24
Figure (2.16): Alamouti Transmitter. ...................................................................... 25
Figure (2.17): Channel effect at the Alamouti scheme. ........................................... 25
Figure (2.18): Alamouti receiver with one receive antenna. ................................... 27
Figure (2.19): The Alamouti scheme performance using BPSK modulation.. ......... 28
Figure (2.20):The transmission phases of General D-STBC. ................................... 32
Figure (2.21): Block diagram of SM transmitter. ..................................................... 33
Figure(3.1): Schematic illustration of QSM transmitter. .......................................... 39
Figure(3.2): BER performance for SM and QSM at 6 bit/s/Hz. ............................... 42
Figure(3.3): System model/ STBC-QSM transmitter. .............................................. 43
Figure(3.4): System model/ STBC -QSM receiver. ................................................. 44
Figure(3.5): BER performance for STBC-QSM (Example3.1), QSM and STBC-SM.
........................................................................................................................... 49
Figure(3.6): BER performance for STBC-QSM (Example3.2), QSM and STBC-
SM. ..................................................................................................................... 50
Figure(3.7): BER performance for STBC-QSM (Example3.3), QSM and STBC-SM.
........................................................................................................................... 50
Figure (4.1): Wireless relaying network model. ....................................................... 55
Figure (4.2): Relaying phase behavior for a relay node. .......................................... 58
Figure (4.3): Example 1, QSM DF-WRN simulation result. .................................... 62
Figure (4.4): Example 2, QSM DF-WRN simulation result. .................................... 63
Figure (4.5): BER performance with different relays, for QSM-DF system.
........................................................................................................................... 64
XI
List of Abbreviations
AF Amplify and Forward
APM Amplitude/ Phase Modulation
AWGN Additive White Gaussian Noise
BER Bit Error Rate
bpcu Bits Per Channel Use
BPSK Binary Phase Shift Keying
CDMA Code Division Multiple Access
CSI Channel State Information
CSM Cyclic Spatial Modulation
DF Decode and Forward
DQSM Differential Quadrature Spatial Modulation
D-STBC Distributed Space Time Block Codes
ECC Error Control Code
EGC Equal Gain Combining
FDMA Frequency Division Multiple Access
FEC Forward Error Correction
GSSK Generalize Space Shift Keying
i.i.d. Independent Identically Distributed
ICI Inter Channel Interference
LTE Long Term Evolution
MIMO Multiple Input Multiple Output
MISO Multiple Input Single Output
ML Maximum Likelihood
MRC Maximal Ratio Combining
MRRC Maximal-Ratio Receiver Combining
OFDM Orthogonal Frequency Division Multiplexing
PEP Pairwise Error Probability
PSK Phase Shift Keying
QAM Quadrature Amplitude Modulation
QPSK Quadrature Phase Shift Keying
QSM Quadrature Spatial Modulation
RF Radio Frequency
RX Receiver
S.E Spectral Efficiency
SAF Selective Amplify and Forward
SC Selection Combining
SDF Selective Decode and forward
SER Symbol Error Rate
SIMO Single Input Multiple Output
SISO Single Input Single Output
SM Spatial Modulation
SMT Space Modulation Techniques
SNR Signal-to-Noise Ratio
XII
SSC Switch and Stay Combining
SSK Space Shift Keying
STBC Space Time Block Codes
STC Space Time Code
STTC Space Time Trellis Codes
TA Transmitted Antenna
TDMA Time Division Multiple Access
TX Transmitter
V-BLAST Vertical Bell laboratories Layered space-time architecture
WRNs Wireless Relaying Networks
Chapter 1
Introduction
2
Chapter 1
Introduction
1.1 Introduction:
Since Marconi‟s experiment in 1897, the telecommunication has dramatically
changed. The new wireless communication paradigms and services developed have
been robustly spread throughout the world. Most notably, the cellular phone system
was evolved throughout five generations (Haykin, 2001). It becomes one of essential
business and a daily-life tool (Rappaport, 2002).This is due to the services offered
and the wire-communication‟s limitations that has been overcome ( Stuber, 2000).
Due to current life-style, it is well-known that there is an urgent need to high-
efficient communication schemes in term of performance and capacity. This is due to
many merged communication applications and services beside traditional voice calls
(Rappaport, 2002). Specifically, researchers focus on finding optimal points given
that the design criteria are the bit error rate (BER) (performance) and the spectral
efficiency (capacity) (Goldsmith, 2005).
However, designing a such robust wireless system faces many challenges such
as spectrum limitations, energy efficiency and user mobility. But the greatest one is
the multipath fading existing in radio communications, this results in not achieving
the Shanon‟s capacity as well as the optimal performance (Rappaport, 2002).The
Mutiple-Input Multiple-output (MIMO) technology has been proposed to provide
enhanced performance and/or better capacity in channels that are experiencing
multipath fading (Goldsmith,2005).This chapter includes the motivation behind the
topic chosen, then the problem statement and literature-review are clarified. Finally
the contributions are summarized.
1.2 Motivation:
The relaying networks (cooperative communication networks) were proposed
to overcome the physical implementation limitations of the MIMO systems. This can
be accomplished by using the multiple distributed single input single output (SISO)
3
system into one virtual MIMO system, without the need to physical implementation
of multiple antennas at the transmitter nor the receiver.
Both space-time block coding and spatial modulation can be adopted
individually or together to offer better performance and higher capacity in WRNs
( Deng & Gao, 2008) , (Narayanan, Di Renzo, Graziosi& Haas, 2016).
One of hot starting points is to consider the very recent SM scheme (namely
Quadrature SM (QSM)) in WRNs. QSM has a great potential to increase the spectral
efficiency and to offer better performance (BER), while preserving the decoding
complexity to the same level. To the best of author knowledge, the research efforts in
either Space-Time-Block-Coded and distributed Quadrature Spatial Modulation are
limited.
1.3 Problem Statement:
It is well known that the node cooperation is an effective technique to yield
significant performance (Liu, Sadek, Su& Kwasinski, 2009). Nevertheless, the key
challenges experienced by MIMO remain in demand. It is to boost the throughput
and improve reliability while preserving low complexity (Goldsmith, 2005). Thus,
this thesis investigates designing/accommodating schemes in order to offer higher
throughput and better performance in WRNs and STBC systems. Considerations that
should be taken in D-STBC design is reducing the code rate and preserving the
single-symbol decoding complexity when more relays are used.
1.4 Research Objectives:
The thesis focuses to satisfy a following goals:
- Design algorithm for an STBC-QSM coding scheme and investigating
numerically and theoretically the performance of the new scheme.
- Exhaustively analyzing case of adapting the QSM to Wireless Relaying
Networks.
- Adapting QSM-STBC to WRNs.
4
1.5 Literature review:
Here, the key research regarding the general thesis‟s background (WRNs,
STBC, and SM) is briefed. However, each chapter has its own recent literature
review. This section is limited to key articles of the general background.
WRNs:
1. In ( Cover & Gamal, 1979), the authors study the relay channels by proving
three capacity theorems for relay channel; utilizing single source single
destination network. To indicate realized capacity, they use superposition
block Markov encoding. The paper also evaluates the capacities of the
Gaussian and certain discrete relay channels. In addition, the lower bound to
the capacity of the general relay channel is implemented.
2. In (Wong,1993), the author presents the design principle of a communication
scheme that supports cooperative problem solving within a network of
knowledge-based systems. The paper solves outstanding issues that related to
cooperative communication systems, such as mechanisms to determine the
sent message, conditions for success of the message, and the ways that are
used to cooperate individual systems with each other for different uses. Also,
the paper proposes two key design principles: the loose coupling of
communication issues, and the notion of communicative acts. Finally,
communication scheme COSMO is implemented to include the previous
ideas.
3. In (Guthery, 1997), a tutorial of relay star networks is presented and a
protocol for wireless data collection on relay star networks is proposed. This
work target the application of data collection on networks for fixed low-cost,
low-data-rate environmental monitors.
4. In (Dong, Li, & Amirnavaei, 2017), a two-hop amplify-and-forward relay
network with energy harvesting nodes are considered, and online joint power
control at the source node and the relay node is designed to maximize the
long-term time-averaged rate through fading channels. The paper subedits the
problem as a joint stochastic optimization problem under battery operational
and finite storage capacity constraints. Simulation results indicate a high gain
of proposed online joint power control algorithm over other methods.
5
STBC:
1. In (Alamouti, 1998), the transmit diversity is presented for the first time,
using two antennas at the transmitter and single antenna at the receiver. The
scheme achieves the same order of diversity of maximal-ratio receiver
combining (MRRC) when using the same number of transceiver antennas. It
is also clarified that the scheme can be extended to two transmit antennas and
more than two receive antennas to attain a diversity order of twice receive
antenna number. It is worth noted that, the proposed scheme does not
consume extra bandwidth and does not require feedback channel from the
receiver to the transmitter and the complexity is similar to MRRC. This work
was the keystone of STBC idea.
2. In (Tarokh, Jafarkhani & Calderbank ,1999), the space-time block coding was
introduced, as a new paradigm for communication using multiple transmit
antennas. The proposed codes took in account the trade-off design factors
which are; achieving the maximum diversity order, obtaining a simple
decoding algorithm and realizing the maximum possible transmission rate.
The paper generalizes STBC to include both real and complex constellations
for any number of transceiver antennas.
3. In (Ganesan, & Stoica, 2001), the space-time block codes are proposed to get
coded diversity for a MIMO communication system. The work casts space–
time codes in an optimal signal-to-noise ratio (SNR) framework and shows
that they achieve the maximum SNR. Also, this paper shows the relation
between the orthogonal designs and space–time codes, and the relation
between generalized real and orthogonal designs.
4. In (Wang,Yue, Qiao & Zhang, 2016), a massive Multiple-Input, Multiple-
Output (MIMO) system with space-time block codes is developed. A base
station equipped with a massive number of antennas is considered and each
user having dual antennas. Simulation results validate the narrowness of the
bounds of the throughput. The error rate performance is also simulated to
obtain the diversity gain for each user.
6
SM:
1. In (Chau & Yu, 2001) the „„space modulation‟‟ principle appeared for the
first time by using more than two antennas to transmit. The proposed space
modulation scheme is called Space Shift Keying (SSK).
2. In (Song, Yang, Xiong, Xie, Jeong & Jiao, 2004) the authors proposed the
modulation scheme called „„channel hopping technique,‟‟ which is named
today as SM – MIMO. The capacity of introduced scheme is shown to be as
using transmit diversity through “flat” channel.
3. In (Mesleh, Haas, Sinanovic, Ahn & Yun, 2008), the terminology of "Spatial
Modulation " was utilized for the first time. In this paper, spatial modulation
is applied to orthogonal frequency division multiplexing (OFDM)
transmission. Aided the presence of different types of channel and
comparisons with various schemes, the performance of proposed scheme is
investigated at different values of spectral efficiency.
There are research efforts that have been proposed to develop the spatial
modulation, some of them improve the performance of the SM by generalizing other
related techniques and other combine SM with other techniques to improve the
performance of the specific applications.
In (Jeganathan, Ghrayeb, Szczecinski & Ceron, 2009); SM – MIMO is
simplified by generalizing the space shift keying (SSK) concept; whereas the spatial
constellation diagram only is used for transmission operation. In (Jeganathan,
Ghrayeb & Szczecinski, 2008), SM–MIMO was developed by providing more than
one transmitted antenna (TA) to be active on every transmission stage, which is
called generalize space shift keying (GSSK). In (Younis, Serafimovski, Mesleh&
Haas, 2010)and (Fu, Hou, Xiang, Yan & Hou, 2010); the authors merge the SM –
MIMO and GSSK- MIMO to enhance the performance. So the result modulation
scheme is called generalize spatial modulation (GSM – MIMO). In (Basar, Aygolu,
Panayirci, & Poor, 2011) the authors propose merging SM – MIMO concept with
Alamouti code to combine between advantages of two techniques. In (Tuan, Ngo,
Mai & Tran, 2012); the paper introduces high-rate Space-Time Block Coded Spatial
Modulation (STBC-SM) schemes for 4 and 6 transmit antennas. In (Li & Wang,
7
2014), the authors present a high rate space-time block coded spatial modulation
scheme with cyclic structure (STBC-CSM).
A high-rate space-time block coded (STBC) spatial modulation (SM) From
error correcting code is presented in (Wang, Chen &Wang, 2014). In (Mesleh,
Ikki & Aggoune, 2015), spatial modulation has been modified to include quadrature
dimension, which is termed as QSM (Quadrature Spatial Modulation).
1.6 Thesis contributions:
The thesis contributions are listed as follow:
A STBC-QSM coding scheme that is basically dependent on Alamouti‟s
STBC code, but can be easily extended to other STBC codes is developed.
The new system allows to activate antennas in quadrature dimension to
contribute in transmitting STBC symbols; as well as in-phase dimension. This
offers a high rate with an understable linear increase in decoding complexity.
Author proposes an algorithm to design STBC–QSM coding scheme. By
theoretical analyzing, and investigating numerically the new scheme
performance, it is shown that the performance of STBC-QSM outperforms
the QSM and STBC-SM. In addition a brief explanation for the basis of
QSM-STBC in WRNs is introduced.
New transmission protocol that adapts quadrature spatial modulation (QSM)
into wireless relaying networks is proposed and this protocol can be exploited
for many WRN scenarios, in order to attain better spectral efficiency and
reliability compared to the state-of-art WRN transmission protocols.
Moreover, both the theoretical and numerical analysis is included.
1.7 Thesis organization:
In Chapter 2, a background of all the basic concepts - that will be used in the
thesis – are analyzed and explained, such as: MIMO, the relaying networks, Space
Time Block Code (STBC), Distributed Space Time Block Code (D-STBC) and
Spatial Modulation (SM).
In Chapter 3, a novel coding scheme, namely, STBC-QSM - is proposed. This
chapter introduces the approach to design the proposed scheme, numerical results,
8
and theoretical analyses for the diversity and complexity order. A brief explanation
for the basis of QSM-STBC in WRNs is introduced.
In Chapter 4, an adaptive QSM transmission protocol that can be used in many
WRN scenarios is proposed. The algorithm of the protocol, followed by theoretical
analysis and numerical results are included.
In Chapter 5, conclusion and summary are listed as well as an expected future
research works are proposed.
9
Chapter 2
Thesis’s Background
(WRNs, STBC, and SM)
10
Chapter 2
Thesis’s Background
(WRNs, STBC, and SM)
2.1 Introduction:
In this chapter the essential concepts of the thesis are explained in three parts.
The first part clarifies the MIMO and relaying networks, followed by Space Time
Block Code (STBC) and Distributed Space Time Block Code (D-STBC) which are
dedicated in the second part, then Spatial Modulation (SM) is clarified in the third
part.
2.2 MIMO Communication System:
MIMO is a communication system where the transmitter and/or receiver
uses multiple antenna in order to achieve better capacity and performance. It tries to
recover the multipath fading effects as allies, not enemies (Rappaport, 1996). This is
done by exploiting these different paths in order to get better reliability and higher
capacity without a need of additional transmitting power or bandwidth (Tse &
Viswanath, 2004). In contrast, the main impediments of MIMO are the cost of added
multiple antennas, the small size of handled units, and the required complexity for
multi-dimensional signal processing. There are several forms of multiple antennas;
conventional wireless communication systems with one transmit and receive antenna
called single input single output (SISO) systems. Whereas systems have multiple
antennas only at the receiver while transmitter has one antenna are named single
input multiple output (SIMO) systems. But systems with multiple transmit antenna
and single antenna at the receiver are denoted as multiple input single output (MISO)
systems. As stated above, systems with multiple antennas at two sides can be
categorized as MIMO systems. General schemes of multi-antenna types are shown
in Figure (2.1). (Plevel, Tomazic, Javornik & Kandus, 2008).
11
Figure (2.1): Multiple - antenna system types.
It should be noted that the MIMO can be exploited to improve performance
(diversity gain) and/or to increase capacity (multiplexing gain) of the wireless
communication system (Plevel, Tomazic, Javornik & Kandus, 2008).
The diversity in wireless communications is applied for disposal of signal
fading. There are several types of diversity, however, all of them follow the same
basic principle: the signal should be transmitted via independent fading paths.
Increasing the uncorrelated degree between the paths, more likely that there is at
least single path is not in severe fade. The diversity can be carried out in three most
common forms which are; space diversity, time diversity, frequency and polarization
diversity. In MIMO systems, the diversity gain can be obtained by a spatial diversity
which can be implemented by multiple antennas equipped at transmit and/or at
receive side (Goldsmith, 2005). The arranged antennas should be sufficiently
separated; otherwise, the transmitted replicas are correlated and the diversity gain is
diminished. The separated distance relies on various factors such as the height of the
antennas, frequency, and the propagation environment. It is worth noting that; in
spatial diversity there is no loss neither in throughput rate nor in bandwidth,
however the tax will be paid is the added complexity due to the used multiple
antennas that has RF chains and need to some processing operations. Based on the
location of multiple antenna; spatial diversity can be divided into transmit and
receive diversity. When multiple antennas are located only at the receive side,
receive diversity is obtained; when multiple antennas are located only at the transmit
side, transmit diversity is obtained. Receive diversity can use one of the several types
of signal combining techniques such as, Selection Combining (SC), Switch and Stay
12
Combining (SSC), Maximal Ratio Combining (MRC), and Equal Gain combining
(EGC) (Tse & Viswanath , 2004),(Brennan, 2003). As well as MIMO systems are
required to exploit multiplexing gain. Spatial multiplexing MIMO systems de-
multiplexes the bit streams into several data chunks which in turn, sent via different
transmit antennas simultaneously as indicated in Figure (2.2). Thus, the data rate of
the system will be maximized without need neither for extra spectrum nor for extra
transmit power. Then each of transmitted signals is received by all of multiple
antennas at the receiver, this complicates the receiver processing, based upon used
algorithm of a receiver decoding. Moreover an MIMO spatial multiplexing system
performance becomes dependent fundamentally on the quality of the receiver. And
by the way, this type of schemes is related to Vertical Bell laboratories Layered
space-time architecture (V-BLAST). (Plevel, Tomazic, Javornik & Kandus, 2008),
(Foschini &Gans, 1996).
Figure (2.2): Block diagram of a MIMO system using spatial multiplexing.
2.2.1 MIMO Channel Model:
Consider a narrowband (flat fading) communication system that has
transmitter antennas, receiver antennas as shown in
Figure (2.3), and let be the channel matrix with entries denotes the gain of the
channel between th transmit antenna and th receive antenna (Deergha Rao, 2015).
At any time instant, let the transmitted signal vector , then the
system can be represented in matrix form as:
⏟
⏟
⏟
⏟
(2.1)
where is the additive white noise vector.
13
Figure (2.3): MIMO communication scheme.
2.3 Cooperative Communication:
As mentioned, the MIMO techniques have played an effective role in
developing the wireless communication performance. This is due to their potentials
in improving spectral efficiency and link reliability (Proakis, 2001). However, it
requires to equip multiple antennas at each of the transmitter and receiver.
Unfortunately; this does not seem suit some of the wireless systems because of the
size and cost limitations. This is because it is not possible to implement physical
multiple-antenna at their small size terminals or surrounding environment may can't
serve MIMO system nature; i.e. there is not enough scattering, and sometimes there
is high correlation between the multiple antennas paths (Liu, Sadek, Su & Kwasinski,
2009) as depicted in Figure (2.4).
Figure (2.4): Hardware constraints of MIMO.
14
Wireless relaying networks (WRNs) have a great potential to override these
limitations. It transforms the single input single output (SISO) system into a virtual
MIMO system without the requiring to equip multiple antennas at the transmitter.
This is by motivating distributed multiple user's nodes to contribute of their resources
synergistically with transmitter to form an array of a distributed antenna. The
random deployment of the client nodes leads to high potential for receiving
uncorrelated signal paths. Cooperative communication is a promising technique for
advanced communication systems such as a long term evolution system (LTE).( Li,
Hu, Qian &Wu, 2012), in addition, cooperative communication gives rise to pure
wireless self-organizing networks without requiring for base stations. It can be used
in several applications of networked embedded systems, e.g. cars use it to
communicate directly with each other, to carrying out various tasks as, exchange
information about accidents, traffic congestion, or bad road situations. Autonomous
robots may employ it to build a wireless network in regions without infrastructure,
e.g., in deserts and in space. Moreover the cooperative communication is considered
a basis of ad-hoc networks, which has several applications (Zhao & Belfiore, 2007).
The cooperative communication networks-or they are termed as wireless relaying
networks (WRNs) - comprise from three parts namely, source (S), relay (R), and
destination (D) (Liu, Sadek, Su& Kwasinski, 2009),(Uysal, 2010) As illustrated
below in Figure (2.5).
Figure (2.5): A simplified cooperation model.
15
The relaying strategy can be modelled with two phases using Frequency
Division Multiple Access FDMA or Time Division Multiple Access TDMA (Liu,
K.J., Sadek, A., Su,W., & Kwasinski, A., 2009) as shown in Figure (2.6):
Phase 1 (Broadcasting phase): The source sends the modulated symbols to
both relays and destination.
Phase 2 (Relaying phase): The relays process the signal which is received in
phase 1 according to the protocol used, then retransmits it to the destination.
It is worth mentioning that the processing operation at the relay nodes subject
to the used relaying protocol.
Figure (2.6): Phases of relaying network (phase 1: brodcastng and phase 2:
relaying).
2.3.1 Common Relaying Protocols:
The relaying protocols are classified into two major groups, fixed relaying
scheme and adaptive relaying scheme (Nosratinia, Hunter & Hedayat, 2004).
16
In fixed ones, the channel resources are shared between the source and relay
nodes in a constant manner. It is characterized by a simple implementation, but it
has the drawback of low bandwidth efficiency and propagation errors. The low
bandwidth efficiency is due to reducing the overall transmission rate which generates
by dividing the channel resources (Liu, Sadek, Su & Kwasinski, 2009). The
propagation errors problem occurs when the channel from the source to the relay
suffers from deep fading. The adaptive relaying tries to overcome the impairments of
fixed relaying by improving performance and efficiency. The fixed and adaptive
protocols will be reviewed in the following subsections based on single-relay WRN
shown in Figure (2.7) (Zhang, Hwachen & Guizani, 2009).
Figure (2.7): Relaying system model.
Figure (2.7) illustrates the system model that will be used to explain the
protocols, as shown, the model comprises a source ), a single relay and a
destination . It is assumed the source and relay transmit equal power, .
The signal reaches at the relay and destination from the source of the
broadcasting phase can be represented by:
√ (2.2)
√ (2.3)
where is the transmitted symbol, are the channel coefficients at the
destination and relay, respectively, from the source, are the additive white
Gaussian noise (AWGN) for the previous channels.
17
While the received signal at the destination from the relay of the relaying phase can
be modelled by :
√ (2.4)
where is the transmitted relay signal based on the nature of the employed
relaying protocol, are the channel gain from the relay to the destination and
AWGN at the same channel, respectively.
2.3.1.1 Fixed relaying protocols:
There are several protocols that can be classified under the fixed relaying. Here
we focus on the Amplify and forward (AF) and decode and forward (DF).
Fixed amplify and forward relaying protocol (AF):
In the AF protocol, the relay amplifies the incoming signal from the source
( , and retransmits the noisy version to the destination as shown in Figure (2.8).
Figure (2.8): Amplify and Forward (AF) relaying protocol.
The AF relay does not require decoding the source signal, that is why it is
considered low complexity and has a low power consumption (Liu, Sadek, Su &
Kwasinski, 2009),(Zhang, Hwachen & Guizani, 2009),(Laneman, Tse & Wornell,
2004). Amplification gain ( ) can be considered the design criteria of the AF
relaying, it mitigates the influence of the channel fading between the source and
relay and can be expressed as (Liu, Sadek, Su & Kwasinski, 2009):
√
√ | |
(2.5)
Therefore , the signal will reach to the destination , and it can be written as :
18
√
√ | |
√
(2.6)
where :
√
√ | |
(2.7)
where is the variance of the complex Gaussian random variable .
It is worth mentioning that the amplification at the relay entails amplifying the
noise, but the destination combines the two information copies that received from the
relay and the source, and makes better decision on the detection of information.
Fixed decode and forward relaying protocol (DF):
Here, the relay decodes the received signal from the source, , re-encodes it,
and then the relay forwards the encoded data to the destination as depicted in Figure
(2.9). The reached signal at the destination from DF relay can be written as
(Liu, Sadek, Su & Kwasinski, 2009):
√ (2.8)
where is the encoded symbol by the DF relay.
The advantage of DF relaying is decreasing the additive noise at the relay
node, but the disadvantage of error propagation - the previous mentioned – that
occurs when the source- relay channel has severe fading. Therefore the decoding at
the relay node is incorrect, this leads to uncorrected decoding at the destination and
degradation of the performance, due to the performance of the system becomes
constrained by the worst connection from the source–relay and source–destination
(Liu, Sadek, Su & Kwasinski, 2009),(Laneman, Tse & Wornell, 2004).
Figure (2.9): Decode and Forward (DF) relaying protocol.
19
Fixed compress and forward relaying protocol (C&F) (Liu, Sadek, Su &
Kwasinski, 2009) , (Zhang, Hwachen & Guizani, 2009):
The basic principle of the compress and forward protocol lies on quantization
the received signal at the relay node from the source , and encoding the samples
into new packets that will be forwarded to the destination. As summarized in Figure
(2.10). The destination combines the transmitted signals from the source and the
compressed version from the relay.
Figure (2.10): Compress and Forward relaying protocol.
Fixed coded cooperation protocol (Liu, Sadek, Su & Kwasinski, 2009)
,(Zhang, Hwachen & Guizani, 2009):
Coded cooperation is a method that combines cooperation into channel coding.
The received signal at the relay node is decoded, extra bits are added, and then the
encoded data is transmitted to the destination as depicted in Figure (2.11). The
redundant bits give the destination more chances to recover the information
correctly.
Figure (2.11): Coded relaying protocol.
20
2.3.1.2 Adaptive relaying protocols:
Using the adaptive mechanism in the relaying networks is of a great value. The
adaptive techniques originates to get rid of the disadvantages of fixed relaying as
low bandwidth efficiency and error propagation as well as to enhance the overall
performance. There is a variety of the protocols that can be classified under the
adaptive protocols. Here the author focuses on the selective Amplify and Forward
relaying (SAF) relaying, selective Decode and Forward relaying (SDF) and
incremental relaying protocol.
Selective decode and forward relaying protocol (SDF):
As mentioned in the DF relaying, relay node handles the received signal in the
fixed manner. In other words, all relays are transmitting even that ones have
erroneous message. This may arises an error propagation problem, especially when a
situation of severe fading is being experienced in the channel between the source
and relay. Selective decode and forward adapts the transmission by utilizing Forward
Error Correction (FEC) technique. The FEC requires adding extra redundancy to the
source node symbols, it gives the relays ability to correct the error without the need
of a reverse channel to request the retransmission of data. The relaying is done only
if the relay detects the symbols correctly (Liu, Sadek, Su & Kwasinski,
2009),(Laneman, Tse& Wornell, 2004),(Farhadi & Beaulieu, 2007).So the relay
nodes should use one of the error detection methods e.g. parity check (Deergha Rao,
2015) to ensure the correct detection.
Selective Amplify and Forward (SAF) (Liu, Sadek, Su& Kwasinski, 2009)
,(Laneman, Tse& Wornell, 2004), (Sun &Li, 2013):
Similar to SDF, the selective amplify and forward (SAF) protocols adapts its
transmissions manner but by using a proper SNR threshold. The relay node
measures the SNR of the received signal with respect to the threshold SNR that is
provided at the relay node. In case; if the SNR of the received signal at the relay
from the source exceeds the threshold value, the relay amplifies the signal, and then
forwards it to the destination, otherwise, the relay will be off. In other words the
relay node amplify only the correct received signal. Figure (2.12) illustrates the
21
principle of SAF protocol for the multiple relays relaying network, as shown at
instantaneous transmission the first relay will be active due to the level of the
signal at the relay 1 exceeds the specific threshold , while the second relay is
idle since the received signal at the relay 2 is below the certain threshold, .
Figure (2.12): Selective Amplify and Forward (SAF) relaying protocol.
Incremental relaying:
In the fixed relaying, the channel resources will be split between the source
and relay compulsively- even though the destination recovers the source transmitted
signal correctly- this leads to diminish the data rate of the system. Incremental
relaying adapts the transmission by coordination between the destination and relay
node via feedback channel. If the destination detects the received signal from phase
1 correctly, there is no need to transmit by relay in phase 2, therefore the relay will
be off. Otherwise, if the destination detects the received signal from phase 1
incorrectly, the relay in phase 2 will be active and uses one of the fixed protocols to
transmit (Liu, Sadek, Su & Kwasinski, 2009), (Laneman, Tse & Wornell, 2004),
(Ikki & Ahmed, 2011).
22
2.3.1.3 Comparison between different relaying protocols:
Figure (2.13) clarifies the comparison between the symbol error rate (SER)
performance of the important relaying protocols (SDF,AF,DF), that were detailed in
previous subsections, and the figure is bounded by the performance of the schemes
that use direct transmission (DT) “no diversity, just a conventional SISO” and use
two transmit antennas. It is evident from the figure that the selective relaying
achieves top performance, it is followed by AF relaying protocol. whereas the DF is
worst one in performance due to the error propagation.
Figure (2.13) :The SER performance of DF, AF, and SDF relaying protocols.
(Meier, 2004).
Figure (2.14) illustrates outage probability - which is the percentage of time
that an acceptable quality of communication is not available (Deergha Rao, 2015 ) -
against spectral efficiency for the mentioned relaying protocols (Liu, Sadek, Su &
Kwasinski, 2009) ,(Laneman, Tse & Wornell, 2004). It is observed that the DF is
23
also worst one in spectral efficiency because of error propagation, while the
incremental relaying achieves highest spectral efficiency, due to its adaptive property
that preserve spectral resources.
Figure (2.14): Outage probability versus spectral efficiency for DF, AF, SDF and
incremental relaying protocols. (Liu, Sadek, Su & Kwasinski, 2009) ,(Laneman, Tse,
& Wornell, 2004).
2.4 Space -time code (STC):
It is well known that the receiver diversity experiences implementation
difficulties in the mobile communications due to the limited size of client‟s device.
Therefore, the need of transmit diversity has arisen as attractive method. There are
different types of diversity as space, time, frequency, and polarization. Combining
space and time diversity with each other creates the concept of space - time code
(STC). It transmits the signal replicas via multiple time slots and antennas to raise
the probability of better receiving, to allow reliable decoding. It is worth noting that
MIMO system, e.g. in case of Alamouti scheme, the Pairwise Error Probability PEP
is inversely related to , while in case of using multiple antennas that transmits
simultaneously, the PEP is inversely related to SNR (Jankiraman, 2004). So the STC
24
achieves more spectral efficiency and reduces the error probability by utilizing the
advantages of the transmit diversity. STCs are classified to space - time block codes
(STBC) and space time trellis codes (STTC). In STTC; the data are encoded using
trellis code, then transmitted through multiple antennas and timeslots. While in
STBC, the encoding operation is performed as block by block which is transmitted
via multiple antennas and timeslots (Vucetic & Yuan, 2003), as indicated in Figure
(2.15). In the following subsection we will discuss the Alamouti STC as basis of
STBC.
Figure (2.15): Illustration of STBC transmission.
2.4.1 Alamouti Space –Time Code (Jankiraman, 2004), (Vucetic & Yuan, 2003),
(Alamouti, 1998):
The basic idea behind space - time block code can be traced back to the
Alamouti schemes that was developed in 1998. It has full rate and achieves
maximum diversity. Alamouti introduced two schemes, two transmitter antenna with
one receiver antenna, and two transmitter antenna with multi receiver antenna. It is
sufficient in this subsection to highlight the Alamouti scheme in the first type with
including encoding and decoding algorithm, and analysing the performance.
2.4.1.1 Alamouti Encoding
At the transmitter side, two-symbol block can be modulated using any type of
modulation, then the two modulated symbols entered the Alamouti encoder
which splits the time period in two, in the first time period, antenna 1 and antenna 2
send simultaneously respectively, whereas in the second time period they
send simultaneously
respectively as shown in Figure (2.16). The coding
matrix of the Alamouti scheme, can be defined as:
25
*
+
(2.9)
where, the columns and rows represent transmit antennas and time slots,
respectively.
Figure (2.16): Alamouti Transmitter.
To preserve the orthogonality, the inner product of the first and second column
is equal to zero. Table 2.1 indicates the summary of encoding process.
Table (2.1): Alamouti encoding process.
Antenna1 Antenna 2
First time slot
Second time slot
The transmitted symbols - via two antennas and two time periods – pass
through Rayleigh fading channel under effect additive white Gaussian noise as
shown in Figure (2.17). Table (2.2) details the parameters of channel and noise :
Figure (2.17): Channel effect at the Alamouti scheme.
26
Table (2.2): Alamouti channel parameters.
Fading gain AWGN noise
Transmit branch 1 Noise in first time slot
Transmit branch 2 Noise in second time slot
It is supposed the fading gains are the constant in the two consecutive symbol
periods (flat fading), for that the channel gains can be written as:
| | (2.10)
| | (2.11)
where are the coefficient gains , | | | | and are the amplitudes
and phases of gain respectively. T is the symbol period .
The received signals at the receiver ( with assumption there is one antenna at
the receiver ) can be expressed as :
* + [
] [
] *
+
(2.12)
where are the received signals at time periods and respectively, and
are independent complex random variables for AWGN noise.
2.4.1.2 Alamouti Decoding
As depicted in Figure (2.18), the Alamouti receiver consists of three parts,
channel estimator to estimate the values of path gains as channel state information
(CSI), signal combiner to mitigate the channel effect in the received signal, and
Mximum liklehood (ML) detector to decide the detected symbol.
27
Figure (2.18): Alamouti receiver with one receive antenna.
The combined signals that enter to ML detector can be written as :
[
] [
] * +
(2.13)
Substituting from equation (2.12) in equation (2.13) about then ,the equation
(2.13) can be written as:
| |
| |
(2.14)
| |
| |
(2.15)
Then, the ML detector decides which symbol was sent, based on the minimum
distance according to the following rule: The transmitted symbol will be if and
only if /
(2.16)
28
2.4.1.3 Simulation result:
The bit error rate (BER) performance of Alamouti is verified through
simulation (Wornell & Trott, 1997). It is evaluated with assuming the fading is
mutual independent between the transmit and receive antennas, and the transmit
power is equal in all simulations. Figure (2.19) indicates the results of BER
performance for Alamouti with single receive antenna, it is clearly seen that the
performance of Alamouti is worse than two branch MRC with 3dB and both have the
same diversity, but actually the performance is equal, the 3dB shift is due to the
transmit diversity in Alamouti that requires dividing power between the transmit
antennas. It is depicted in the same figure the performance for Alamouti with two
receive antennas and 4 branches MRC, the diversity is also the same, but the
performance of Alamouti is shifted by 3dB due to the same reason above.
Figure (2.19): The Alamouti scheme performance using BPSK modulation.
(Wornell & Trott, 1997).
2.4.2 Space Time Block Coding:
As stated before, the Alamouti scheme can be generalized to create the STBC
scheme. With the same idea; the STBC encoding process is modelled mathematically
by the what known as code matrix, where each column represents one antenna and
each row represents a time slot as shown in (2.17). The coding matrix is designed
29
by taking in account each column is orthogonal to other; for sake of simple decoding
(Tarokh, Jafarkhani & Calderbank, 1999).
[
]
(2.17)
where is the transmitted symbol from antenna in time slot , represent
number of time slots and transmit antennas respectively.
The code rate of an STBC is defined as the ratio between the number of symbols
( ) to be entered an STBC encoder per time slots ( (Tarokh, Jafarkhani &
Calderbank, 1999).
(2.18)
2.4.3 Distributed Space Time Block Coding:
To reap the benefits of an STBC and MIMO, applying an STBC over the
wireless relaying network is developed to generate the term: Distributed Space Time
Block Code (D-STBC) (Li, 2004). The D-STBC system achieves diversity order and
has the advantages of transmission reliably and high spectral efficiency, using virtual
transmit antennas which is deployed through the relay nodes.
2.4.3.1 D-STBC definition:
D–STBC is a transmission scheme where STBC‟s sequences are created using
the relay nodes in distributed manner in WRNs. In WRNs, each relay represents a
single antenna, hence it transmits one column of the STBC matrix which is defined
above. e.g. the relay, transmits the column of the STBC matrix ,
Mathematically speaking (Dohler, Hussain, Desai& Aghvami, 2004); let and –
where n = 1 ,…., N - are the matrices belonging to the relay , then the vector
transmitted by the relay is determined by :
(2.19)
30
In other words; will generate the un-conjugated and conjugated symbols of the
nth
column of STBC matrix.
2.4.3.2 D-STBC with using Alamouti (Deng & Gao, 2008), (Li, Ge, Tang& Xiong ,
2008):
In this subsection, the author details applying Alamouti scheme- due to its
simplicity- over wireless relaying network (WRN). Consider the relaying network
consists of a source node, two relays , and a destination node . Each of them
contains single antenna . The adopted protocol is selective decode and forward (SDF)
due to its performance.
As any relaying system, the D-STBC can be modelled over two phases:
Phase1 (broadcasting phase): Here, the source sends the data represented by two
symbols for each transmission process – due to Alamouti – to relay nodes and
destination. Here, all equations are written for one transmitted tuple. The signal
reached at the destination can be expressed as :
[
] [
] [
] (2.20)
where are the signal from source to destination, transmitted
symbol and AWGN, respectively, and each of them at the symbol . is the gain
of the channel from source to destination .
The signal that reaches the and can be expressed as:
[
] [
] [
] (2.21)
[
] [
] [
] (2.22)
The notations at (2.21), (2.22) are the same in the (2.20) but they from source
to relay 1 and relay 2.
Phase 2 (Relaying phase): The relays use SDF protocol that assumed the relay
decodes only the correct received data, also it is assumed that ,
31
so the decoded data at relay 1 is the same at relay 2 and can be represented with
where
After that, the relay re-encodes the two symbols according to the Alamouti, the
resultant code matrix becomes:
*
+
(2.23)
Therefore, the relay 1 transmits the first column of the code matrix in (2.23),
whereas the second column is transmitted by relay 2.
2.4.3.3 General D-STBC :
As the Alamouti was generalized to higher order STBC, it can be generalized
applying STBC with any order to relaying network. This can be modelled as
depicted in Figure (2.20), the system consists of a source (S), relay nodes
( , and a destination D. In the phase 1, the source transmits symbols
- according to the order of the used STBC- to the relay
nodes and destination. With the same assumptions when using Alamouti; In phase 2,
the relay processes the received data by decoding; to result
[
, and by re- encoding; to result the code matrix
that combat with the used STBC. In the meantime; each relay transmits one column
of the code matrix (Deng & Gao, 2008).
32
Figure (2.20): The transmission phases of General D-STBC.
2.5 Spatial Modulation (SM):
Spatial Modulation is a transmission mechanism that merges digital
modulation and multiple antennas transmission to improve the throughput of MIMO
systems. The Spatial modulation aimed to expand the modulated signal constellation
to include the spatial dimension; by this, information can be transmitted using
antenna indices, moreover amplitude/ phase modulation (APM). The active antenna
is represented as part of the original information to be transmitted, thus the spectral
efficiency is boosted. At any signalling time instance, only one antenna can transmit
data, and other will transmit zero power, so it uses single Radio frequency (RF) chain
in transmission, and there is no need to synchronize the transmit antennas. This
reduces the complexity and cost as well as avoids inter channel interference (ICI) at
the receiver (Renzo, Hass, Ghrayeb, Sugiura& Hanzo, 2014),(Mesleh, Haas,
Sinanovic, Ahn& Yun, 2008).
33
2.5.1 SM transmitter (Renzo, Hass, Ghrayeb, Sugiura & Hanzo, 2014),(Mesleh,
Haas, Sinanovic, Ahn& Yun, 2008) :
Consider MIMO system with a modulation constellation size, where
are the transmit and receive antennas, respectively, in general,
SM uses two kinds of constellation, the first one is signal constellation Phase Shift
Keeing / Quadrature Amplitude Modulation (PSK/QAM), and the second one is
spatial constellation. As shown in Figure (2.21); the transmission is executed by
transmitting one of the two symbols ( ) explicitly, while transmitting the other ( )
implicitly by finding an active antenna index in each transmission stage. The rate of
SM is:
(2.24)
where the first group of bits choose the index of an active transmit
antenna, whereas the second group of bits are mapped according to the
corresponding -ary signal constellation .
Figure (2.21): Block diagram of SM transmitter.
For example : Let the MIMO system is with = 4 and QPSK. The transmission
process has a rate of RSM = log2(4) + log2(4) = 4 bits / channel use ( ). So the
encoder will modulate 4 bits at each channel use. Let the incoming data bits are
"1100”; the first = 2 bits (11) determines the active transmit antenna, while
the second = 2 bits (00) defines the transmitted QPSK symbol. Then, this
process is repeated for the next data block as indicated in table ( 2.3).
34
Table (2.3): SM mapping for 4bit/s/Hz. (Mesleh, R. Y. , Haas, H., Sinanovic, S.,
Ahn, C. W. , & Yun,S., 2008).
Antenna index
Input bits
Transmit symbols
1 2 3 4
0000 1 0 0 0
0001 j 0 0 0
0010 -1 0 0 0
0011 0 0 0
0100 0 1 0 0
0101 0 j 0 0
0110 0 -1 0 0
0111 0 -j 0 0
1000 0 0 1 0
1001 0 0 j 0
1010 0 0 -1 0
1011 0 0 -j 0
1100 0 0 0 1
1101 0 0 0 j
1110 0 0 0 -1
1111 0 0 0 -j
2.5.2 SM receiver (Renzo, Hass, Ghrayeb, Sugiura & Hanzo, 2014),(Mesleh, Haas,
Sinanovic, Ahn& Yun, 2008):
The symbol that is emitted by the specific active antenna at any channel use;
travels via a communication channel which offers a specific "channel signature or
finger print”, this means that the impulse response is unique with respect to the same
symbol transmitted by other transmit antenna (TA). This leads to simple distinguish
of the signal at the RX.
35
The signal vector – that has dimension is transmitted over
wireless channel that contains set of vectors, each of them represent the channel
gains between the transmit antenna and receive antennas. This can be expressed as :
[
]
(2.25)
The received signal, at each receive antenna is written as :
(2.26)
where N is AWGN matrix.
Thus; the receiver (RX) employs the unique signature of the wireless channel
to extract the information bits. The modulator searches through all the expected
combinations of channel responses and modulation symbols and performs the
decision according to lowest Euclidean distance (Maximum likelihood).
2.6 Conclusion:
In this chapter; the main issues of the thesis topic are reviewed which are the
MIMO, relaying networks, Space Time Block Code (STBC), Distributed Space Time
Block Code (D-STBC) and Spatial Modulation (SM).
36
Chapter 3
Space-Time Block Coded
Quadrature Spatial
Modulation
37
Chapter 3
Space -Time Block Coded Quadrature Spatial Modulation
Quadrature spatial modulation (QSM) has been recently introduced for
MIMO communication systems. It is proposed to enhance the data rate of
conventional spatial modulation (SM) techniques by using an additional modulation
spatial dimension. Combined with Space time block code (STBC), the overall
spectral efficiency and the communication reliability can be enhanced. This is
because an additional modulation dimensions (space-time) are introduced which
allows for a transmit diversity. This chapter introduces a STBC-QSM coding
technique that is basically dependent on Alamouti‟s STBC code but can be easily
extended to other STBC codes. Unlike QSM, a transmit diversity of 2nd order or
higher can be obtained. Both diversity and complexity of the proposed design is
analysed and compared to state-of-art schemes. Simulation results, which corroborate
the theoretical ones, show the effectiveness of STBC-QSM scheme proposed in
improving the overall performance and the spectral efficiency.
3.1 Introduction:
In the last decade, there has been a rising interest in developing new
systems to enhance the signal quality in conventional MIMO systems. Since the
seminal work of (Telatar, 1999), systems with multiple transmit/receive antennas
have become an essential tool to achieve power efficiency and high spectral
efficiency in wireless communications. Recently, Space Modulation Techniques
(SMT), like spatial modulation (SM) (Mesleh, Haas, Sinanovic, Ahn& Yun, 2008)
are attracted a significant research interest. That techniques attains features over
conventional MIMO in terms of energy, performance and complexity.
Not long ago, the Quadrature Spatial Modulation (QSM) has been introduced
as an emerging technology in the future MIMO wireless networks (Mesleh, Ikki &
Aggoune, 2015). In QSM, an extra spatial-constellation dimension can be indexed
and used to modulate the data. This enhances the achieved throughput while
preserving the key features of standard SM. However, it has no transmit-diversity,
despite the fact that multiple transmit-antenna is simultaneously active in the
transmission process. This chapter proposes an STBC-QSM coding approach that is
38
basically dependent on the Alamouti code but can be easily extended to other STBC
codes. It achieves better performance as transmit-diversity is obtained.
A thorough search of the relevant literature indicates that no research efforts
have been introduced to tackle the transmit-diversity issue of QSM despite the fact
that multiple transmit-antenna is simultaneously active in the transmission process,
except (Yigit &Basar, 2017)and (Wang,Chen, Gong&Wu,2017). Unlike our scheme
proposed, the code of (Yigit &Basar, 2017) and (Wang,Chen, Gong&Wu,2017) are
designed particularly to Alamouti‟s STBC configurations and hence it is limited to
achieve a transmit-diversity order of two only. For the best of author knowledge,
there is no way to extend this code to other configurations, while it is straightforward
in our case. Also, it is limited to systems with transmitting antennas higher than 3
antennas.
Theoretical analyses are included to show the robustness of the introduced
scheme. A thorough search of the relevant literature indicates that no research efforts
have been introduced to tackle the transmit-diversity issue of QSM. This chapter is
organized as follows: QSM scheme is explained, then system model is introduced,
followed by the proposed algorithm to design an STBC-QSM code. Combined with
numerical results, theoretical analyses for the diversity and complexity order is
included. Finally a breif explanation for the basis of QSM-STBC in WRNs is
introduced.
3.2 Quadrature spatial modulation (QSM):
Quadrature spatial modulation (QSM) has been recently reported as a novel
spectral and energy efficient transmission paradigm classifying at the space
modulation techniques [(Mesleh, Ikki& Aggoune, 2015). It aims to overcome the
deficiencies of conventional SM by enhancing the spectral efficiency with no extra
tax. Unlike the conventional SM, QSM utilizes two spatial-constellation dimensions;
in-phase and quadrature, to modulate the spatial symbols. The symbol constellation
is further chunked into real and imaginary components which are transmitted through
the in-phase and quadrature dimensions, respectively. Hence; QSM improves the
spectral efficiency over conventional SM . Using two dimensions for transmission in
QSM, does not cause inter–channel interference (ICI) at the receiver input, since the
39
two transmitted data are orthogonal and modulated on the real and imaginary parts of
the carrier signal. Moreover the QSM overcomes other conventional MIMO
drawbacks that related to performance and hardware complexity issues. Thus, QSM
outperforms SM (Mesleh, Haas, Sinanovic, Ahn & Yun, 2008) in term of throughput
while preserving the inherent features of standard SM.
3.2.1 QSM transmitter (Mesleh, Ikki & Aggoune, 2015):
Consider MIMO system, where are the number of transmit and
receive antennas, respectively with . Let the number of the incoming bits
to be transmitted is ; where is the modulation constellation
size. The transmitted bits are classified into three groups, the first two groups each
contains bits and modulates the two spatial constellation symbols, whereas
the third group contains and modulates the signal constellation symbol –
using conventional signal modulation (PSK/QAM) - which is further decomposed
into real and imaginary components. Then, and are transmitted
individually through the antennas and, which are activated according to first
and second groups bits, respectively.
Figure(3.1): Schematic illustration of QSM transmitter.
For more illustration, Let the MIMO system is with =2 and 4-QAM. Then
the system has 4 spectral efficiency. So the encoder will modulate 4 bits at
each channel use. Consider the data bits W= [ 0 1 1 0].
40
The first two bits [ 0 1], will be mapped by 4-QAM modulator to
( ), whilst the remaining two bits will indicate the two active antennas, by
using the spatial constellation – see Figure (3.1) - , the first active ( ) are
modulated by bits [ 1 ], while the second active ( ) are modulated by
bits [ 0 ], this means that the real part of the modulated symbol (-1) will
transmit through , while the imaginary part ( j) will transmit via , hence; the
transmitted vector is determined by = [ ] = Then, this process is
repeated for the next data block as indicated in the mapping table ( 3.1 ).
Table (3.1) : QSM mapping for 4bit/s/Hz. (Mesleh, Ikki & Aggoune, 2015).
Antenna index
Input bits
Transmit symbols
1 2
0000 -1-j 0
0001 -1 -j
0010 -j -1
0011 -1-j
0100 -1+j 0
0101 -1 j
0110 j -1
0111 0 -1+j
1000 1-j 0
1001 1 -j
1010 -j 1
1011 0 1-j
1100 1+j 0
1101 1 j
1110 j 1
1111 0 1+j
41
3.2.2 QSM receiver (Mesleh, Ikki & Aggoune, 2015):
The transmitted symbol signal crosses over wireless channel
which can be modelled by a complex channel matrix with dimension . For
any element of it, denotes to the complex channel path gain between the
transmit antenna and receive antenna. The channel entries are assumed to be
Independent Identically Distributed (i.i.d.) complex Gaussian random variables with
zero mean and variance .
The signal reached at the input of the receiver can be formulated as follow:
⏟
=√ ( ⏟
⏟
⏟
⏟
⏟
(3.1)
where denotes the transmitted energy, , are the
,
columns of the
channel matrix respectively, where and
is a complex Gaussian noise vector with zero mean and variance
.
Based on the optimal ML decoder, and assumed CSI is available at the receiver, the
detected signal is written as :
[ ]
‖ √ ‖ (3.2)
3.2.3 Comparison between SM and QSM performance:
Here, the BER performance of QSM (Mesleh, Ikki& Aggoune, 2015) and
conventional SM (Mesleh, Haas, Sinanovic, Ahn & Yun, 2008) is compared at the
equal spectral efficiency (6 bit/s/Hz) as shown in Figure (3.2). It can be noticed that
the QSM achieves about 3 dB gain over SM. As mentioned, this improvement is
achieved almost without cost, due to the receiver complexity of both the QSM
scheme and the SM are the same and related to the adopted spectral efficiency.
42
Figure(3.2): BER performance for SM and QSM at 6 bit/s/Hz.
(Mesleh, Haas, Sinanovic, Ahn & Yun, 2008) , (Mesleh, Ikki& Aggoune, 2015).
3.3 System model:
An MIMO communication system is considered, with .
Assume each block of the incoming stream has the length of ⌊ ⌋
bits and is divided into two parts, where denotes the number of possible transmit
antenna combinations (refer to step (2) of Section 3.4) as depicted in Figure (3.3).
The first part ({ } bits) is modulated using M-QAM/PSK and then
encoded using an STBC scheme. If is an STBC coding matrix, it is
divided into real matrix part and imaginary matrix part where
T is the signalling period Time for the STBC block, and is the number of the
used transmit antennas. If represents the encoded symbols number in then the
code rate r of the adopted STBC is expressed as (Alamouti,
1998) ,(Tarokh, Jafarkhani & Calderbank, 1999). The second part is ( bits)
where c are the possible combinations of the active transmit antenna indices that are
used to transmit the or . Both encoding and antenna-index processes (STBC-
QSM coding) is further detailed in Section (3.4). These matrices and are
transmitted over a wireless channel H which has dimension- as shown in
43
Figure(3.4), and faces an additive white Gaussian noise, . The received signal is
given by:
⏟
√ ⏟
⏟
⏟
⏟
⏟
(3.3)
where denotes the transmitted symbol energy, ,and represent the and
channel matrix that contains columns of H that corresponding to the antennas
used in transmitting the real and imaginary parts, respectively, and is the number
of the active antennas that is used to transmit the or ( < ).
Figure(3.3): System model/ STBC-QSM transmitter.
Equivalently, (3.3) can be re-written as follow:
⏟
√
⏟
⏟
(3.4)
where is the equivalent channel matrix that includes the channel coefficients of
the antenna set used for transmission. .
Hence, the optimum ML detector can be carried out using:
‖ ‖
(3.5)
where is the adopted modulation constellation.
44
Figure(3.4): System model/ STBC -QSM receiver.
3.4 The proposed STBC-QSM coding scheme:
Here, an approach to design STBC – QSM coding scheme is proposed. The
Alamouti's STBC has been chosen, this is because of its optimality (code-rate ( )
& full-orthogonality) and simplicity. However, the scheme proposed can be easily
extended to other types of STBCs.
Step1. Assuming a transmitter equipped with antennas and the system
supports antennas that can transmit the or ( < ). is
determined from the adopted STBC matrix. At glance, let assume that
Alamouti‟s STBC is used and hence =2.
Step2. Determine the number of codewords that will be transmitted ( )
from: (
)
, .
Step3. Generate all possible combinations of the codewords without
repetition.
Step4. Construct ⌈
⌊ ⌋⌉ codebooks - by selecting the
codewords that satisfy on each codebook, where is a
codeword from codebook , . This condition can be disregarded if
higher data-rate is preferred while lower performance can be
accommodated.
Step 5. Create a table containing the assignment of each codeword (STBC-
QSM matrix) from C to a binary vector as shown in Table 3.2.
45
Step6. Multiply each group of codewords
by where are phase-rotation angles. The
rotations are optimized to maximize the diversity and coding gains and to
prevent rank deficiency between overlapping codewords. Where
, where is the minimum coding gain distance (CGD)
(Jafarkhani, 2005).
Example 3.1: 3-STBC- QSM, 8 –QAM (4bpcu):
Let the MIMO system is with =3 which transmit the Alamoutie STBC, and
the modulation type is 8-QAM. Then the system has 4 spectral efficiency. So
the encoder will modulate 8 bits at each channel use (due to two time slots in the
Alamouti). According to the previous algorithm, there are four codebooks ,each of
them contains one codeword , this means that C= 4, shifted by a rotation angles
, consequently each antenna combination is represented by 2 bits as shown in
table (3.2). Consider the data bits W= [ 0 1 1 0 0 1 1 1]. The first two bits
[ 0 1], determines the two pair active antennas, by using the spatial constellation, the
first pair is the first and second antenna, while the second pair is the second and third
antenna, whilst the remaining six bits [1 0 0] and [1 1 1] will be mapped by 8-QAM
modulator to ( ) and ( ), then real parts of wil be
transmitted as alamouti code matrix via first and second antenna , while imaginary
parts of will be transmitted as Alamouti code matrix via second and third
antenna.
Table(3.2): The mapping table for a code in example 3.1.
0(00) 0 0
1(01) 0.4
2(10) 0 0.8
3(11) 0 1.2
where and . defines the antenna set to be used to
transmit the real and/or imaginary parts of the transmitted symbols.
Example 3.2: 4-STBC- QSM, 16 –QAM (5.5 bpcu):
46
Table (3.3): The -mapping table for a code in example3.2.
0(000) 0 0 0
1(001) 0 0
2(010) 0.8
3(011)
4(100) 0 0 1.2
5(101) 0 0
6(110) 0.4
7(111)
Example 3.3: 4-STBC- QSM, 16 –QAM (6bpcu):
In this example, the orthogonality condition between codewords is not taken in
consideration. This allows higher data rate in the spatial dimension. The mapping
table for a constructed code is given in table (3.4).
Table(3.4): The mapping table for a code in example3.3.
0(0000) 0 0 0
1(0001) 0 0
2(0010) 1.02
3(0011)
4(0100) 0 0 0.695
5(0101) 0 0
6(0110) 1.099
7(0111)
8(1000) 0 0 1.32
9(1001) 0 0
10(1010) 0.525
11(1011)
12(1100) 0
, 0.496
13(1101)
, 0
14(1110) 0
, 0.326
15(1111)
, 0
47
3.5 Performance Analysis: 3.5.1 Diversity Analysis:
Assuming that x is a codeword that is transmitted and h is the channel-
coefficients vector and is the SNR in the system, the conditional pairwise error
probability (PEP) of the STBC-QSM can be calculated as (El Astal, Abu-Hudrouss,
Salmon & Olivier, 2015) ,(Simon, & Alouini, 2000)
| √
‖ ‖
(3.6)
where ∫ ⁄
is the complementary error function. The error matrix
is evaluated by . Equation (3.6) can be simplified as
| (√
‖ ‖
)
(3.7)
where =diag
and denotes the singular values of . is a
unitary matrix and It is observed that no rank deficiency in for the case of
STBC-QSM due to phase rotation applied, hence . This can be proved by
numerical search-loop to find . Therefore, (3.7) can be bounded as
( (√ ∑
‖ ‖
) ) ( (
√ ∑ ‖ ‖
) )
(3.8)
According to Lemma 1 of (Ju, Song & Kim,2009), the unconditional PEP is
approximated for high SNR by:
∏
(3.9)
∏
(3.10)
It can be observed that, the diversity gains achieved is and hence a gain of
is preserved.
3.5.2 Complexity Analysis:
The detection complexity is analysed here in terms of the number of iterations
needed to find an estimate for the receiving signal. The order of complexity for the
optimal ML decoder shown in (3.5) is , where is the number of symbols
per STBC matrix and is the modulation order. This order is reduced to .
48
In contrast, the conventional QSM of (Mesleh, R., Ikki, S., & Aggoune, S., 2015)
have a lower complexity of ( )
,However, this marginal
penalty in complexity is paid off in term of better performance achieved. In addition,
reduced-complexity decoder can be used to combat this penalty (Al-Nahhal, Dobre,
& Ikki, 2017), (Jun, Xueqin, Yier, Wenjun, Sangseob & Moon Ho, 2017), (El Astal,
Abu-Hudrouss, Salmon& Olivier, 2015), (De Lamare, 2013).
3.5.3 Efficiency Analysis:
Hence, the spectral efficiency (S.E) of the Alamouti STBC-QSM scheme is:
= [ +
] /2 = , Dividing by 2 due to two channel uses
codebook matrix. It is worth noting that the S.E of STBC-QSM outperforms S.E of
the Alamouti scheme { } with { } bit/s/Hz, and it is better than S.E of
STBC- SM { + 0.5 } with {0.5 } bit/s/Hz, due to QSM
advantage over SM.While the S.E of STBC-QSM outperforms S.E of the QSM{
( ),where ( )
.This can be summarized in table (3.5):
Table(3.5): Comparison of spectral efficiency for different systems.
Alamouti STBC-SM QSM STBC-QSM
Spectral Effciency + 0.5 ( )
3.6 Simulation results:
In this section, the author shows numerical results of the STBC-QSM
simulation using MATLAB, and makes comparison between the proposed scheme
and other systems to investigate the performance of the proposed scheme. The
previous examples are simulated with assumptions that the adopted channel is
Rayleigh fading channel and four antennas at the receiver are supposed for all
comparisons. The curve of bit error rate (BER) performance as a function of SNR is
considered in simulation results, and BER value of is taken as the reference
value of comparison. The STBC-QSM system uses the optimal decoder.
49
In Figure (3.5), the BER performance of STBC-QSM with considerations in
the Example 1; is evaluated and simulated, for 8-QAM, 4bit/s/Hz spectral efficiency.
The performance of QSM scheme (Mesleh, Ikki& Aggoune, 2015)and SM- STBC
system (Basar, Aygolu, Panayirc & Poor, 2011)are depicted at 4-QAM and 8-QAM
respectively, both achieving similar spectral efficiency, i.e. 4 bit/s/Hz. It can be
observed that; the performance of STBC-QSM outperforms QSM and SM-STBC
with 1 dB and 2.5 dB respectively. It is important to note that STBC-QSM scheme is
simulated for odd number of antennas, and satisfied high performance, while that can
not be used in QSM scheme.
The results depicted in Figure (3.6), are for the STBC-QSM in the Example
3.2; where it is evaluated for 16-QAM with 5.5 bit/s/Hz spectral efficiency, it is
compared with BER performance of QSM scheme (Mesleh, Ikki& Aggoune,
2015)and SM- STBC (Basar, Aygolu, Panayirc & Poor, 2011) that are simulated by
2-QAM and 16-QAM respectively, both have 5 bit/s/Hz spectral efficiency. It is
evident from the Figure (3.6) that; the performance of STBC-QSM provides again
over QSM and SM-STBC about 3 dB and 4 dB respectively, although the STBC-
QSM has higher spectral efficiency.
Figure(3.5): BER performance for STBC-QSM (Example3.1), QSM and STBC-SM.
50
Figure(3.6): BER performance for STBC-QSM (Example3.2), QSM and STBC-SM.
Figure (3.7): BER performance for STBC-QSM (Example3.3),
QSM and STBC-SM.
Figure(3.7): BER performance for STBC-QSM (Example3.3), QSM
and STBC-SM.
51
Figure (3.7), investigates the BER performance of the STBC- QSM scheme
with taking into account the assumptions of the Example 3.3 in section 3.4, which
allowed for the non-orthogonal codewords exist at the same codebook, Here, STBC
– QSM is simulated with 16-QAM under the spectral efficiency of 6 bit/s/Hz. It can
be noted that the performance of STBC-QSM degrades about 2 dB with respect to
STBC-QSM scheme under the spectral efficiency 5.5 bit/s/Hz (example2); this due
to non orthogonality issue, in contrast the scheme with non-orthogonal code words
achieves higher throughput as mentioned in the previous section.
3.7 Distributed Space – Time Block Code Quadrature Spatial
Modulation (D-STBC-QSM):
Adapting space-time block codes to wireless relaying networks, termed as
Distributed-STBC have been developed to overcome the MIMO limitations and to
get better reliability (Li, 2004). In the current work, only QSM has been adopted in
WRNs, and explained in details in chapter 4. However, the adaption of the proposed
QSM-STBC into WRNs has not been developed in the current work and will be
further studied in the future. Nevertheless, a brief explanation for the basis of QSM-
STBC in WRNs is introduced in this section.
The transmission is carried out through two phases; broadcasting and relaying,
in broadcasting phase the source transmits the symbols to the destination and relay
nodes, the number of transmitted symbols is based on the order of the used STBC,
e.g in Alamouti; the source must transmit two symbols. Relaying phase depends on
the nature of the used protocols (SDF-DF-AF…etc.), and it is based on the proposed
STBC-QSM algorithm, where the bits received at a relay nodes are divided into three
groups. The first group is modulated using M-QAM/PSK and then encoded using an
STBC scheme, then STBC code matrix is divided into real matrix part and imaginary
matrix part. The second and third groups determine the relays that will transmit the
real and imaginary STBC code matrices. Applying example (3.2) on D-QSM-STBC;
let the WRN has four single antenna relays which transmit the Alamouti STBC, and
the modulation type is 16-QAM. Then the system has 5.5 spectral
efficiency(considering orthogonality condition). So the encoder will modulate 11 bits
at each channel use (due to two time slots in the Alamouti). According to the STBC-
QSM algorithm, there are four codebooks, each of them contains two codewords, this
52
means that C=4,shifted by a rotation angles
, consequently each relay combination is represented by 3 bits as shown in table
(3.3). Consider the data bits W= [ 0 1 1 0 0 0 1 0 0 1 0]. The first three bits
[0 1 1], determines the two pair active relays, by using the spatial constellation, the
first pair is the third and fourth relay, while the second pair is the first and second
relay, whilst the remaining eight bits [0 0 0 1] and [0 0 1 0] will be mapped by 16-
QAM modulator to ( ) and ( ), then real parts of
will be transmitted as Alamouti code matrix via third and fourth relay, while
imaginary parts of will be transmitted as Alamouti code matrix via first
and second relay.
3.8 Conclusion:
Due to the increased need to improve the capabilities of MIMO schemes, a
novel STBC scheme based on QSM has been proposed in this chapter. The new
system allows to active antennas in quadrature dimension to contribute in
transmitting STBC symbols; as well as in-phase dimension. This offers high rate
with an understable linear increase in decoding complexity. By theoretical analyzing
and investigating numerically the performance of the new scheme, it is clarified that
the performance of STBC-QSM outperforms the QSM and STBC-SM. A brief
explanation for the basis of QSM-STBC in WRNs is introduced.
53
Chapter 4
Quadrature Spatial
Modulation for Wireless
Relaying Networks
54
Chapter 4
Quadrature Spatial Modulation for Wireless Relaying Networks
This chapter introduces a transmission protocol that adapts quadrature
spatial modulation (QSM) into wireless relaying networks, in order to obtain
better spectral efficiency and reliability compared to the state-of-art WRN
transmission protocols. In addition, it is analysed theoretically to corporate
the included numerically simulation.
4.1 Introduction:
In the last decade, the space-diversity has seen much research interest
due to better reliability and higher-throughput. As mentioned in Chapter
two, the Multiple-Input Multiple-Output (MIMO) scheme needs to establish
multiple antennas at the transmitter and/or receiver to get un-correlated
signals at the destination. However, the limitations of size and cost may
make the MIMO schemes impractical in many wireless communications
systems (Goldsmith,2005). To override these limitations the wireless
relaying network has been proposed (Liu, Sadek, Su & Kwasinski, 2009).
The wireless relaying networking (WRN) scheme motivaties neighbouring
distributed multiple user's nodes to contribute of their resources
synergistically with transmitter to form an array of a distributed antenna.
Thus, a virtual MIMO scheme is created. Likewise MIMO scheme, the
WRN has a great potential to enhance the performance, reliability and
spectral efficiency of the wireless communication systems but without
facing the difficulties of MIMO physical deployment. Different transmission
protocols have been introduced in literature to manage the communication in
both the transmitter-relays and the relays-receiver links . Recently, the
quadrature spatial modulation has been proposed for conventional MIMO
communications systems (Mesleh, Ikki & Aggoune, 2015). In MIMO-QSM,
the spatial dimension extended to in-phase and quadrature dimension to
modulate the real-part and the imaginary-part individually and hence the
overall throughput enhanced. Recently, there are few research efforts that
have been proposed to validate the performance of the very limited WRNS
55
scenarios based on QSM. In (Afana, Mesleh, Ikki & Atawi, 2015), the
authors analysed the performance of QSM-WRN with a multi-antenna at the
source, single-antenna amplify and forward (AF) relays, and single-antenna
destination. In (Afana, Erdogan & Ikki, 2016), authors considered the QSM
with decode- and forward (DF) WRN that has only a single multi-antenna
relay. In this chapter, an adaptive QSM transmission protocol that can be
exploited for many WRN scenarios is proposed. It achieves a significant
performance improvement as well as enhances the overall system
throughput. Moreover, both the theoretical and numerical analysis is
included. This chapter is arranged as follows: System model is firstly
introduced, then the adaptive protocol is proposed, followed by theoretical
and numerical results.
Figure (4.1): Wireless relaying network model.
4.2 System model:
An WRN communication system, with multiple-antenna source ,
L number of relays , each relay has antennas, and the
destination with antennas is considered, as depicted in Figure (4.1),
56
where . This configuration is denoted by ( , , ). The
transmission is conducted through two phases, see Section (4.3). Similar to
conventional WRN transmission protocols, the first phase (broadcasting
phase) is where the source is transmitting while both the relay and
destination are receiving. In the second phase (relaying phase), the source is
in silent mode while the relays are transmitting to the destination. It has been
assumed that the network is experienced a Rayleigh fading channel for both
the source-relays and relays-destination links. Also, the receiving node is
supposed to have perfect channel state information (CSI).
4.3 The proposed transmission protocol:
This section discusses the adaptive transmission protocol proposed in
this chapter. The transmitting process can be carried out in two phases that
are described in details as follows:
A. Broadcasting phase
The source transmits using an
appropriate channel encoding scheme, where ‟s are M1-ary PSK/QAM
modulated symbols, denotes the information block index and m is the
number of symbols in the broadcasting phase. Thus, the received vector at
is:
⏟
⏟
⏟
⏟
(4.1)
where is the equivalent channel matrix of S - link based on the t/m-rate
coding scheme used, with entries ∼CN(0, 1),where CN is the complex normal
distribution.
The vector is the noise at with entries ∼ CN(0,√ ).
The determining an appropriate channel encoding scheme relates to
the number of antennas at the source and relays and other issues, but this
falls out the scope of this study and may be introduced in future works.
In addition, the source should use an error control code (ECC) scheme
to maximize the number of active relays that will be involved in the next
57
transmission phase. This is to detect and/or mitigate any error experienced
by data while transmission to the relays (see IEEE 802.16j standard of
(Genc, Murphy, Yu, & Murphy, 2008).
B. Relaying phase
As mentioned, a relay will not participate in this phase if it has
erroneous information. To brief the discussion, it is considered that a fixed
number out of relays will always have no errors.
Initialization:
Among all sharing relays, assign a unique number for
each relay‟s antenna. This is conducted when the transmission operation is initiated
by higher layer functions within the WRN depend on constraint of network (desired
rate, latency, etc.).
Procedures:
The participating relays will each behave the following procedures on its r
= ×log2 bits received as shown in Figure (4.2):
1. The bits received are sectioned into three chunks. The first two chunks
contain and bits individually. The third chunk contains
bits, where M2-ary PSK/QAM modulation scheme is used in the relaying
phase. It should be noted that ( ). If r + , the
excess bits must be buffered .
2. Then, the and bits are multiplexed based on the relay‟s mapping-
table ,see the mapping-table (4.1) and table (4.2), to determine whether this
relay is idle node or it will participate in the relaying phase. If so, proceeds to
the next step, else the relay is settled down immediately.
3. The third group of bits is modulated using M2-ary PSK/QAM , to yield
– which is further divided to real and imaginary
components.
4. Given , and components, the relay is transmitting through
antenna/s as shown in the below tables .
58
Fig
ure
(4.2
): R
elay
ing p
has
e beh
avio
ur
for
a re
lay
node.
59
For more illustration, in Figure (4.2), the incoming bits and will be used to
check if the undergoing relay should be active or not in the upcoming phase - so it is
converted to decimal values by a binary to decimal converter (Bi2De) - if yes, these
bits will experience the whole process shown, otherwise, the operation will be
terminated regarding this relay.
Example 4.1: QSM- relaying network 1:
Consider WRN with two relay, each relay has single antenna
, according to the previous algorithm, then ( ) , this
means that the antenna combinations are represented by two bits as shown in
table(4.1) , e.g. bits of antenna combination is 01, this means that , the real part of
modulated symbol will be transmitted through first relay, while the second relay
transmits the imaginary part of modulated symbol.
Table(4.1): The code-mapping table for example 4.1.
0 1
0(00)
1(01)
2(10)
3(11) 0
Example 4.2: QSM- relaying network 2:
The example is shown below in table (4.2).
Accordingly, the received signal at the D assuming perfect time-
synchronization (Chang & Kelley, 2012) is given by:
⏟
⏟
⏟
⏟
⏟
⏟
(4.2)
where { ∼ CN(0, 1)} are the channel coefficients for the link relay‟s
antenna – destination that is used to transmit the and components,
60
respectively. The vector { ∼ CN(0,√ ) is the noise at .
Thus, the optimal ML detector at the destination considers a concentrated search
for all expected transmitted signal vectors. This is written as:
[ ]
‖ ‖ (4.3)
Table (4.2): The code-mapping table for example 4.2.
2 3
(0)0000 0 0
(1)0001 0 0
(2)0010 0
(3)0011 0
(4)0100 0 0
(5)0101 0 0 0
(6)0110 0 0
(7)0111 0 0
(8)1000 0 0
(9)1001 0 0
(10)1010 0 0 0
(11)1011 0 0
(12)1100 0 0
(13)1101 0 0
(14)1110 0 0
(15)1111 0 0 0
4.4 Diversity analysis:
It is well-common that the diversity gain is determined by SNR-order appeared
in the pairwise error probability (PEP) formula of the system considered. Logically,
the PEP of DF-WRN is defined by:
61
(4.4)
where are the PEP through broadcasting and relaying phase, respectively.
is the error probability of single-chain of S-Relays links. It is identical to the
MIMO scheme derived in (Simon & Alouini, 2000) and is given by:
(
) ∑ (
) (
)
(4.5)
where n denotes the information block index, and √
, is the average SNR
per bit.
is identical derivation of QSM scheme shown in (Mesleh, Ikki & Aggoune,
2015), that is given by :
√ (
)
(4.6)
Where is the Gamma function.
and:
{
| |
| | | |
| |
| |
| | | |
| |
| | | |
| |
| |
(4.7)
where denotes the transmitted energy .
Clearly, × and order is maintained for the broadcasting and relaying
phases, respectively.
4.5 Simulation results:
The bit-error-rate (BER) performance of the QSM DF-WRN is evaluated in
this section, for different spectral efficiency values. It is compared with conventional
SM DF-WRNs (Mesleh, Haas, Sinanovi´c, Ahn& Yun, 2008), (Narayanan, Di
Renzo, Graziosi & Haas, 2013) to show the achieved performance improvement. The
simulation uses 4-antenna destination with numerous configuration for the relays and
BER value of is taken as the reference value of the comparison. Without loss
62
of generality, the network considers only the relaying part, in other word, all relays
have a non-erroneous data.
Figure (4.3) considers ( , , ) DF WRN with Example 4.1‟s code and it
uses 4-QAM, hence 4 bit/s/Hz spectral efficiency is achieved. It can be observed that
nearly a 2.5 dB SNR gain is offered by the proposed protocol compared to the SM
DF relaying system.
Figure (4.3): Example 4.1, QSM DF-WRN simulation result.
In Figure (4.4), the BER simulation result of ( , , ) network is shown with
Example 4.2‟s code. It uses 4-QAM, hence 6 bit/s/Hz spectral efficiency is achieved.
As expected, it can be observed that the proposed protocol provides about 4.5 dB
over SM-DF relaying system. As mentioned in chapter three these improvements are
almost without cost, due to the same level of receiver complexity of both the QSM
scheme and the SM and related to the adopted spectral efficiency. (Mesleh, Ikki &
Aggoune, 2015).
63
Figure (4.4): Example 4.2, QSM DF-WRN simulation result.
To show the effectiveness of relay‟s number increases, the BER performance
of the QSM-DF WRN for a various number of relays, with is
depicted in Figure(4.5), also it uses 4-QAM and achieves different spectral
efficiencies (4, 6, 8 and 10 bit/s/Hz respectively). The degradation of the
performance that noted is marginal and is understandable. This results due to the
increasing of relay number that leads to reducing the coding gain that can be offered
and hence performance is degraded.
64
Figure (4.5): BER performance with different relays, for QSM-DF system.
4.6 Conclusion:
QSM has an effective role in improving the spectral efficiency and the
performance of the MIMO systems. This chapter exploits the QSM to develop the
capabilities of the relaying system, by implementing QSM on the multiple relays
with multi- antenna, without complexity cost at the destination. By theoretical
analyzing and investigating numerically, it is shown that the performance and gain of
the proposed protocol and scheme outperform the state-of-art WRN transmission
protocols.
65
Chapter 5
Conclusion and Future
Works
66
Chapter 5
Conclusion and Future works
5.1 Conclusion:
The thesis has been focused on developing quadrature spatial modulation for
space -time block coding and for wireless relaying networks. The desired objectives
of the thesis are accomplished by adoption two tracks which are; design the STBC-
QSM scheme and applying the QSM on the wireless relaying network. An STBC
scheme based on QSM is proposed; the new system relies on the Alamouti but it can
be generalized to higher order coding schemes. STBC-QSM obtains higher spectral
efficiency and enhances the reliability, this is investigated by theoretical analyzing,
and simulation results which verified the performance of the STBC-QSM
outperforms the QSM and STBC-SM. Moreover, a brief explanation for the basis of
QSM-STBC in WRNs is introduced.
In addition an adaptive transmission protocol that adapts quadrature spatial
modulation (QSM) into wireless relaying networks is introduced, the BER
performance of the proposed protocol is simulated and the diversity is analyzed, it is
very clear that the new protocol achieves better spectral efficiency and reliability
compared to the state-of-art WRN transmission protocols.
Now, it is safe to say that; we get efficient quadrature spatial modulation
system for space-time block coding and for wireless relaying networks, which enjoys
with high performance and overcomes various constraints that exist in other systems.
67
5.2 Future Works:
Design an adaptive transmission protocol for effective exploiting diversity
and multiplexing gains in wireless relaying networks. This can be carried out
by applying STBC-QSM scheme on the wireless relaying networks.
Investigating the performance of using STBC-QSM in WRNs.
Using low complexity detection strategy for STBC-QSM systems.
Implement STBC-QSM with a higher order of STBC to improve the BER
performance by achieving higher transmit diversity gain.
Implement high rate STBC-QSM with cyclic structure to improve the spectral
efficiency of STBC-QSM systems while preserving the same transmit
diversity order.
Combining STBC-QSM with Code Division Multiple Access (CDMA) to
exploit the benefits of STBC-QSM technique for high number of users.
Using Differential Quadrature Spatial Modulation (DQSM) with STBC to
reap the advantages of STBC-QSM without the need to CSI.
68
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