scma: a survey on advancement towards 5g...
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SCMA: A Survey on Advancement towards 5G
Communications
Madhura Kulkarni1 and Dr. Rajeshree Raut2
1 St.Vincent Pallotti College of Engineering & Technology,
Nagpur, -441108, {[email protected]} 2 Shri Ramdeobaba College of Engineering & Management,
Nagpur, {[email protected]}
Abstract. The requirement to connect large number of users efficiently led to
the refinement in wireless communication from second generation to fifth
generation. The enhancement of cellular communication system involves use of
various multiple accesses. This article aims at elaborating the multiple access
techniques progressing from 2G -5G and describes SCMA Sparse Code
Multiple Access one of the NOMA (Non-Orthogonal Multiple Access)
techniques used in 5G cellular communication system. It is a codebook based
multi-dimensional non-orthogonal spreading technique. It involves combining
of QAM mapper and spreading signature blocks into a single block of a SCMA
spreading encoder having SCMA codebook set that results in a multi-
dimensional codeword. This paper describes the basic design of the encoder and
decoder along with the concept of codeword used in it. It also explains the link
implementation for the SCMA for its application.
Keywords: SCMA; LDS; non-orthogonal multiple-access; multi-dimensional
constellation; 5G; LTE.
1 Introduction
The 5G wireless communication involves diverse applications, which will be
deployed by 2020. The most important requirement of 5G is its high spectral
efficiency. Apart from that high throughput, better service, quality, low control
signaling and lower latency are some of the requirements to be met while using any
access. In a cellular system the channel bandwidth is limited whereas, it has to
accommodate maximum users in it, thus multiple access is a technique that helps the
cellular communication to be more economical by maximum utilization of channel
bandwidth as a physical layer technology. It enables the wireless base stations to
identify various users and serve them.
The different ways that allowed access to the channel included mainly orthogonal
and Non-orthogonal access. In orthogonal access the cross correlation of signals from
different users is zero [1], which can be achieved by Frequency Division Multiple-
Access (FDMA), Time Division Multiple-Access (TDMA),Code Division Multiple-
Access (CDMA), Orthogonal Frequency Division Multiple Access(OFDMA) Non-
orthogonal schemes allow non-zero cross correlation among the signals from different
Advanced Science and Technology Letters Vol.147 (SMART DSC-2017), pp.487-498
http://dx.doi.org/10.14257/astl.2017.147.68
ISSN: 2287-1233 ASTL Copyright © 2017 SERSC
users [1], such as in random waveform Code-Division Multiple-Access (CDMA) [2],
Trellis-Coded Multiple-Access (TCMA) [3] and Interleave Division Multiple-Access
(IDMA) [4]. Power Domain Multiple Access, Low Density signature OFDM
(LDMA), Pattern Division Multiple Access (PDMA), Building block sparse
constellation based Multiple Access (BOMA), Sparse Code Multiple Access (SCMA)
and Lattice Partition Multiple Access (LPMA) [7] and many more. The multiple
accesses used in communication from 2G-5G is shown in Fig.1
�
Fig. 1. Multiple access Techniques used in the communication system
The 2G communication system made use of basic multiple access that is, TDMA
and FDMA wherein the users are scheduled on orthogonal time slots.TDMA is a
multiple access method which allows different users to use the same channel
bandwidth by dividing the transmitted signals from the users into the different time
slots.
Fig. 2. TDMA where channel bandwidth is orthogonal to time in time-frequency and code
domain [11]
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FDMA is a multiple access method in which the channel bandwidth is divided
completely according to the number of users. Thus, the complete channel bandwidth
is utilized by the user for the specific time period.
Fig. 3. FDMA where channel bandwidth is orthogonal to frequency in time-frequency and code
domain [11]
The 3G communication system later made use of CDMA where the channels are
non -orthogonal in frequency and time domain but orthogonal in code domain. Code-
division multiple access (CDMA) is a multiple access method where different
transmitters can send the signals simultaneously over the same channel bandwidth
Fig. 4. CDMA where codes are orthogonal to frequency & time in time-frequency and code
domain [11]
The 4G communication systems, widely known as Long Term Evolution (LTE)
makes use of OFDMA, where the users are orthogonal in 2D frequency-time domain.
Orthogonal resources are occupied by the users for communication. Being the access
with single user detection it becomes comparatively easy for implementation. Here
the subsets of sub-carriers are assigned to the individual user. It is derived from
OFDM, that is Orthogonal frequency division Multiplexing that aims at allocating the
users in time domain only, where as OFDMA aims at allocating the users in both time
and frequency domain as shown in the Fig.5.1 and Fig 5.2 respectively.
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Fig. 5.1. OFDM Fig. 5.2. OFDMA
As a result of limited users of orthogonal resources, which is proportional to the
number of users, 5G communication system has led to the extensive research on
various multiple accesses, that can meet the three basic demands as per 3G
Partnership Project (3GPP) [5][6], which includes massive Machine type
Communication (mMTC) [5][6], Ultra reliable & Low Latency communication and
enhanced vehicle-to-everything (eV2X) communications [5][6]. To achieve the same,
5G communication systems require large connectivity with good throughput and
spectral efficiency [7]. These challenges can be addressed by introducing NOMA
techniques.
The Table.1 shows the comparison of frequently used schemes in NOMA [7] with
their multiplexing advantages and disadvantages. In a communication system various
channel properties of the communication link are referred to as Channel State
Information (CSI), which is one of the important parameters responsible for the
quality of wireless communication systems. If CSI is not estimated properly, cross
layer interference limits the potential performance gain of MU-MIMO [8]. If we
compare various NOMA techniques listed in the Table.1 we can conclude that LDS-
CDMA, LDS-OFDMA and SCMA are the techniques where CSI is of least
importance, hence are more desirable. In this paper we will be focusing more towards
the study of SCMA.
Table 1. Comparison of various Access Techniques in NOMA [7]
Schemes Characteristics Advantages Disadvantages
Power-Domain
NOMA
Power Domain
Multiplexing
High SE, Compatible to
other techniques
Need user pairing Error
propagation in SIC
LDS-CDMA Sparse spreading
CDMA
No Need of CSI, Near
optimal MPA detector
Redundancy from
coding
SCMA Sparse spreading
Multidimensional
constellation
No Need of CSI, Near
optimal MPA detector,
More diversity than simple
LDS
Redundancy from
coding,
Difficult to design
optimal code book
LDS-OFDM Sparse spreading
OFDM
No Need of CSI,
Near optimal MPA
detector, More
fit for wide-band than
LDS-CDMA
Redundancy from
coding
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PDMA Sparse spreading
Multiplexing in
power code and
spatial domain
More Diversity, Near
optimal MPA detector,
low complexity receiver
Redundancy from
coding,
Difficult to design
optimal patterns
BOMA Tiled Building block Simple structure
compatible to current
system low
complexity receiver
Need user pairing Not
very flexible.
LPMA Multilevel lattice
code Multiplexing in
power and code
domains
No Need of user clustering Specific Channel
Coding
2 Need for SCMA
SCMA does not require the CSI for the transmitter and the receiver in the
communication link. It is also responsible for reducing the interference in MU-MIMO
to enhance the link performance [8]. It enables grant free transmission with low
overhead & low latency for sporadic small packet transmission [8]. The QAM
modulation and the LDS spreading are replaced by multi-dimensional codebooks in
SCMA [10]. Despite of large number of users the collisions are less and have better
coverage because of the spreading gain. The Table.2 gives the comparison of main
aspects of LDS and SCMA which makes use of Message Passing Algorithm (MPA)
[11]detector at the receiver with same structure and complexity over the codewords
and symbols.
Table 2. SCMA Vs LDS [9]
Schemes SCMA LDS
Multiple
access
yes Codebook Domain yes Signature Domain
Sparse yes Sparse codewords yes Low Density
Signatures
Coding Gain yes Data carried over
multi-dimensional
complex
codewords
No Data carried over
QAM symbols
Degree of
Freedom
J codebooks each with
M codewords
J Signatures
Receiver Codeword-based MPA Symbol- Based MPA
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3 SCMA: An Introduction
SCMA [9] is a multidimensional codebook based access, based on non-orthogonal
technique, introduced by Huawei Technologies. In this access, the incoming bits are
directly mapped into multidimensional code words and are transmitted across the
channel. The implementation of Link level simulation for SCMA requires only few
modifications to be done on the LTE transceiver [16]. At the receiver end to reduce
the complexity of decoding and avoid the interference of the channels, MPA is used.
SCMA is a technique used in 5G communication system for economic, energy
efficient link layer performance and low complexity implementation [12]. CDMA is a
multiple access in which the data is spread out over orthogonal code sequences. LDS
(Low Density Signature) is a more advanced approach of CDMA. In CDMA, the
CDMA signature expands to a QAM symbol generated from QAM mapper. Whereas
SCMA involves clubbing of QAM mapper and CDMA spreader as shown in Fig.6.
Fig. 6. Clubbing of QAM Mapper with CDMA spreader [9]
At transmitter the multi-dimensional codeword’s are formed by mapping the coded
bits directly in complex domain and codeword’s from different users are overlapped
non- orthogonally in sparse spreading way. Signal detection is done by the receiver
which is then followed by channel decoding for data recovery.
3.1 SCMA System Model
There are J user layers in this system. The signal of each user layer is spread into k
orthogonal resource layers. SCMA transmits the signal in an overloaded manner, i.e.
λ. The log |M| input binary bits bj with unique codebook Xj ⊂ ℂ k are mapped into a
k-dimensional codewords Xj. The codeword’s mapped by input bits correspond to the
codebook of the user layer where different codebook is owned by different users. The
design of encoder involves two steps as shown in Fig.7 and described as given below:
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i) Binary bits b j are modulated to d bits from (d0: dN), where g j will be the
modulating generator matrix represented by
dj=bj(gj) . (1)
ii) K-N zeros are mapped in the Xj codeword which is k-dimensional with V j ⋵ B,
k*N matrix as shown in Fig.9, thus expressed as
Xj=Vj(dj) . (2)
Fig.7. Fixed Up-Link SCMA System Model [15]
The SCMA Encoder F shown in Fig.8 maps symbols from V users (1: V) where
each symbol b v is represented by M bits. Codeword is represented as a point in a
modulation constellation where the bv consists of 3 bits; each point in it is represented
by a complex number (r, Ө).
The codeword itself is represented as a very sparse matrix, which determines
where the 3 encoded bits will be transmitted on the available sub-channels (carriers).
This matrix is denoted by B matrix as shown in Fig.9 i.e. B , kxM assuming F
available channels where we use only M bits. Thus B is a matrix, consisting of 0s and
1s where the 1s represent the places where there is transmission.
To construct B we can start with Identity matrix I so that it maps the m symbols to
M codewords. Then all zero columns are inserted to make the matrix sparse.
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Fig. 8. V=6, M=4, F=4 [14]
Consider an example for the above design shown in Fig.8 using tanner graph and
the sparse Matrix as shown in the Fig.9
Fig. 9. Tanner Graph and matrix
Number of 1s in each column is denoted by dk that is number of users from which
each subcarrier accepts the data, whereas the number of 1s in each row is denoted by
dv. Table 3 shows the variables used in the tanner graph shown in Fig.9
Table 3. Variables used in Tanner Graph
V 6 No of Layers F=k 4 Number of functional nodes i.e. available subcarriers M 4 Length of codeword in number of bits dv 2 Maximum k nodes connected to each V node (No of
used subcarriers) dk 3 Maximum V nodes connected to each k node λ (k-1)/2=1.5 Overloading Factor
3.2 Design of Codebook
The design of codebook for SCMA is supposed to be joint optimization of multi-
dimensional constellation design, which makes this access unique than the other
NOMA techniques. The basic aim of the codebook design is to maximize the shaping
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gain by providing good distance properties in the multidimensional constellation. It
should also have less projection points over each resource element. Multi-dimensional
codebook design has been studied in different aspects and a generalized method to
design a codebook of SCMA system is given in [18]. The Codebook initially was
designed on the basis of 8-QPSK constellation. Another approach of designing an
efficient codebook was using star-QAM signaling constellation [20], which helps in
improving the BER without hampering low detection complexity. A Multi-
Dimensional SCMA Codebook Design Based on Constellation Rotation and
Interleaving [19], which proposes lower BER than the low density signature in down-
link Rayleigh fading channels. The spherical code method, is another approach that
improves the system performance, in order to build mother multidimensional
codebook [21]. The designing equation of the codebook for SCMA is given by [9]:
V *, G*= arg maxV,Gm(S (V,G; J,M,N,K)) . (3)
Where m is the design criterion, in order to achieve sub-optimal solution for this
multidimensional problem, a multi-stage optimization approach is proposed.
SCMA aims at reducing the complexity of SCMA detectors. The detection can be
realized by finding the maximum joint posterior probability of all users’ transmitted
symbols. As a result of enormous computations practical implementation is
hampered. Hence, the Message Passing Algorithm (MPA) [22], which is used in LDS
[23][24] based on the sum-product algorithm [25] is used by SCMA detector to
reduce computation.
In order to reduce the complexity, fixed-point implementation of the log-domain
message passing algorithm (Log-MPA) [26] was implemented. Another proposed
approach used two receivers [27], which simplified the detection structure but also
curtailed exponent operations quantitatively in logarithm domain [15]. Low
complexity of detection and low complexity detection structure due to the codebooks
[28] is studied for the receiver. Fixing t codeword’s in the mth iteration [29] is a
simplified detector based on Partial Marginalization, (IPM-MPA) detector for the
fixed up-link SCMA system. Thus IPM-MPA is more computational efficient than
PM-MPA [29].
3.3 SCMA Link Implementation
By doing minor modifications in the LTE transceiver the link level simulations for
SCMA are implemented. As shown in Fig.10, the change made in the transmitter is
done by replacing the QAM modulator and the DFT block by SCMA encoder which
maps the coded bits into multidimensional codeword. The spreading factor of these
transmitted bits can be seen from the tanner graph as shown in the Fig.9. As seen in
the transmitter only by making few modifications in the LTE receiver, the receiver of
SCMA is designed by replacing single user channel equalization and QAM de-
mapper with SCMA decoder of each layer. Tanner graph constructed by the
codebooks are performed by the MPA algorithm. It starts with the initial conditional
probability calculation at each function node.
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Then it enters MP iterations between the function node and the variable node. For
each iteration, both the nodes are updated; this is done independently by each pair.
After several sufficient iterations LLR (Log Likelihood ratio) for coded bits are
calculated based on codeword probability & output at variable node and can be given
as the input to the turbo decoder. Thus the user to user communication in SCMA can
be studied through the Fig.10, and its block diagram is shown in Fig.11.
Fig. 10. Uplink Implementation for SCMA at the transmitter end as compared to OFDMA
transmitter [17]
Fig. 11. SCMA implemented in transmitter and receiver [17]
4 Conclusion
This paper explains the progress of wireless communication towards SCMA as a
promising technology for 5G wireless communication. First, the necessity of SCMA
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with its comparison with other NOMA techniques as well as other accesses is briefed
then, structure, encoding, multiplexing, codebook design and link implementation
techniques are described. Connectivity, high spectral efficiency and low complexity
are studied as the key features of SCMA. Sparsity of multi-dimensional codewords
for low complexity of joint detection with high performance at the receiver end can be
resolved with the help of MPA algorithm.
5 Future Scope
FPGA implementation of the encoder and the decoder design can be done for the
practical implementation. Bit Error Rate (BER) vs Eb/No curve can be enhanced as
the bit streams can be decoded with the average BER less than 0.001 (namely at most
1 bit error in the total 1000 bits [17]. Complexity of the receiver can be reduced by
enhancing the encoder design as well as by implementing Max Log MPA at the
receiver. The formation of new codebook can also be one of the factors responsible
for enhancing the transmission. The codebook with other constellations can also be
formed, the Euclidean distance between the points of which satisfies the requirement
stated.
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