stfc report

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A

Project reportOn

Implementation

Of PRE-DFT processing for MIMO OFDM

with space time frequency coding


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-------------- UUNNIIVVEERRSSIITTYY CCOOLLLLEEGGEE OOFF EENNGGIINNEEEERRIINNGG

---------- UUNNIIVVEERRSSIITTYY CCOOLLLLEEGGEE OOFF EENNGGIINNEEEERRIINNGG,, HHYYDDEERRAABBAADD


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CCEERRTTIIFFCCAATTEE

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PPRREE DDFFTT PPRROOCCEESSSSIINNGG FFOORR MMIIMMOO OOFFDDMM UUSSIINNGG SSTTFFCC

IIss aa bboonnaaffiiddee wwoorrkkddoonnee bbyy

The students of M.Tech in Electronics and Communication Engineering during the

year 2009-2010 as a partial fulfillment of the requirement for the award of M.Tech

degree by -------- University College of Engineering, Hyderabad.

((IInntteerrnnaall GGuuiiddee)) ((HHeeaadd,, DDeepptt ooffEECCEE))


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AACCKKNNOOWWLLEEDDGGEEMMEENNTT

We are grateful to Department of Electronics and Communication Engineering,

University college of Engineering, Hyderabad, Which gives us the opportunity to have

profound technical knowledge. Theyre by enabling us to complete the project.

We express our sincere and heartful thanks to ------- (PRINCIPAL university

college of engineering Hyderabad) for his kind permission to undertake this project work.

We are extremely grateful to ----- (HOD of ECE, university college of

Engineering ,Hyderabad) for her valuable suggestions and timely help in the endeavor

and which paved the way for the successful completion of this project.

We specially surrender humble thanks and record our deep sense of gratitude to

our guide, who helped us a lot, guided us in excellent way by keeping us always in

positive mood and our wills alive. He is none other than ------------.

Last but not least, we express our heartfelt thanks to all this staff members and

friends for all help and co-operation extended in bringing out this project successfully in

time.


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Abstract

Subcarrier based space processing was conventionally

employed in Orthogonal Frequency Division Multiplexing (OFDM) systems under

Multiple-Input and Multiple-Output (MIMO) channels to achieve optimal performance.

At the receiver of such systems, multiple Discrete Fourier Transform (DFT) blocks, each

corresponding to one receive antenna, are required to be used. This induces considerable

complexity.

In this project, we propose a pre-DFT processing scheme

for the receiver of MIMO-OFDM systems with space-time-frequency coding. With the

proposed scheme, the number of DFT blocks at the receiver can be any number from one

to the number of receives antennas, thus enabling effective complexity and performance

tradeoff. Using the pre-DFT processing scheme, the number of input signals to the space-

time-frequency decoder can be reduced compared with the subcarrier based space

processing. Therefore, a high dimensional MIMO system can be shrunk into an

equivalently low dimension one.

Due to the dimension reduction, both the complexity of

the decoder and the complexity of channel estimation can be reduced. In general, the

weighting coefficients calculation for the pre-DFT processing scheme should be relevant

to the specific space-time-frequency code employed. In this paper, we propose a simple

universal weighting coefficients calculation algorithm that can be used to achieve

excellent performance for most practical space-time-frequency coding schemes. This

makes the design of the pre-DFT processing scheme independent of the optimization of

the space-time-frequency coding, which is desirable for multiplatform systems.


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11..11IINNTTRROODDUUCCTTIIOONNDeployment of high performance wireless networks presents a

number of technical challenges, this include the regulatory limits on usable radio

frequency spectrum and a complex time varying propagation environment like multi path.

Now a days there is a huge demand for the networks with the high data rates and a better

quality of service (QOS).In this scenario there arises a few drop out in the connections

and hence there is a requirement for boldly innovative techniques that improve both

spectral efficiency and link reliabilities. Usage of multiple antennas at the receiver and

transmitters in a wireless networks is a rapidly emerging technology that promises higher

data rates at longer distances without consuming extra bandwidth or transmitter power.

Recent inventions on the smart antennas provide a wide variety of

options ranging from single input multiple output (SIMO) ,to the multiple input multiple

output(MIMO) architectures that open up multiple data pipes over a link. The number of

inputs and the outputs here refers to the number of antennas at the transmitter and the

receivers .The space time modem at the transmitter modulates the information bits to e

conveyed to the receiver and maps the signals to be transmitted across the space and time.

The space time modem at the receiver processes the signals on each of the Mr receive

antennas according to the transmitters signaling strategy and demodulate and decodes the

received signal.


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Different smart antenna architectures provide different benefits which can be broadly

classified as array gain, diversity gain, multiplexing gain and interference reduction.

The signaling strategy at the transmitter and the corresponding processing at the receiver

are designed based on link requirements (data rate, range, reliability etc.). For example, in

order to increase the point to- point spectral efficiency (in bits/sec/Hz) between a

transmitter and receiver, multiplexing gain is required which is provided by the MIMO

architecture. The signaling strategy also depends on the availability of channel

information at the transmitter. For example, MIMO does not require channel knowledge

at the transmitter, although it enjoys improved performance if channel information is

available. On the other hand, spatial division multiple access (SDMA) does require

channel information at the transmitter which is used to increase the network throughput at

the media access (MAC) layer. The advantage of point-to-multipoint SDMA over point-

to-point MIMO is that SDMA deploys multiple antennas only at the cellular base station

or wireless local area network (LAN) access point.


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MULTIPLE ANTENNA MODEL

Consider a MIMO system with Mt transmit antennas and Mr

receive antennas as shown in Figure below or simplicity we consider only flat fading; i.e.,

the fading is not frequency selective. When a continuous wave (CW) probing signal, s, is

launched from the jth

transmit antenna, each of the Mr receive antennas sees a complex-

weighted version of the transmitted signal. We denote the signal received at the ith

receive antenna by hijs, where hij is the channel response between the jth transmit antenna

and the ith

receive antenna. The vector [h1j,h2j,hMrj]T

is the signature induced by the jth

transmit antenna across the receive antenna array.

It is convenient to denote MIMO channel(H) in matrix notation asH= [ h11 h12 h1MT

h21 h22 h2MT

hMRMT]


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The channel matrix H defines the input-output relation of the MIMO system and is also

known as the channel transfer function. If a signal vector x=[x1,x2,..xMt]T is launched

from the transmit antenna array then the signal received at the receive antenna array can

be written as Y=Hx+v

Where v is the Mr*1 noise vector consists of independent complex-Gaussian distributed

elements with zero mean and variance Note that the above channel matrix can be

interpreted as a snapshot of the wireless channel at a particular frequency and at a

specific instant of time. When there is rich multipath with a large delay spread, H varies

as a function of frequency. Likewise, when the scatterers are mobile and there is a large

doppler spread, H varies as a function of time. With sufficient antenna separation at the

transmit and receive arrays, the elements of the channel matrix H can be assumed to be

independent, zero-mean, complex Gaussian random variables (Rayleigh fading) with unit

variance in sufficiently rich multipath. This model is popularly referred to as the

Gaussian MIMO channel. In general if antennas are separated by more than half the

carrier wavelength (/2), the channel fades can be modeled as independent Gaussian

random variables.

BACKGROUND

MIMO systems promise much higher spectral efficiency than SISO systems. MIMO

systems can also be leveraged to improve the quality of transmission (reduce error rate).

This section will focus on MIMO signaling schemes that assume perfect channel

knowledge at the receiver and no channel knowledge at the transmitter.


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Space-time trellis codes

For a given number of transmit antennas, the code design objective is to construct

the largest possible codebook with full diversity gain (L=Mt) and the maximum possible

coding gain. A number of hand-crafted STTCs (space-time trellis codes) with full

diversity gain were first provided. Full diversity codes with greater coding gain were then

reported, where codes were found through exhaustive computer searches over a feed

forward Convolutional coding (FFC) generator. New codes were then presented by

searching for the codes with the best distance spectrum properties. The distance spectrum

of a codebook counts how many pairs of code words are located at a given product

distance for the codeword pair.

To provide some insight into all these codes, the frame error rate for

two transmits antennas over an iid Gaussian channel. As a reference, a linear space-time

block code (STBC), with and without a concatenated AWGN trellis code.

Linear Space Time block codes

Since linear codes are easier to encode and decode, we will focus on the

design of linear codes here. A linear code is defined as a set of code words that are linear

in the scalar input symbols. Complex valued Mt modulation matrices K are

used to spread the input information symbols over MtT spatio-temporal dimensions. The

real and imaginary part of each input symbol Skis modulated separately with the matrices

Akand Ak+k/2


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This framework can be extended to non-linear codes by modulating the modulation

matrices with nonlinear functions of the input symbols. For example, for K=3, the

following vector of input symbols leads to a nonlinear space-time code

Modulation and coding for MIMO

The signal design did not include effects of concatenated coding.

MIMO technology is compatible with a wide variety of coding and modulation schemes.

In general, the best performance in achieved by generalizing standard (scalar) modulation

and coding techniques to matrix channels. MIMO has been proposed for single-carrier

(SC) modulation, direct-sequence code division multiple access (DS-CDMA) and

orthogonal frequency division multiplexing (OFDM) modulation techniques. MIMO has

also been considered in conjunction with concatenated coding schemes. Application of

turbo codes and low density parity codes to MIMO has recently generated a great deal of

interest, as have simpler coding and interleaving techniques such as bit-interleaved coded


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modulation (BICM) along with iterative decoding. Inclusion of concatenated codes along

with soft Viterbi decoding is in fact essential for realizing the full diversity gain of

practical MIMO systems.

CHAPTER 2

INTRODUCTION AND BACKGROUND TO OFDM

OFDM proposals were made early in the 1960s and 1970s. It took more

than a quarter of a century for this technology to move from the research domain to the

industry. The technique seems to be very simple but involves many complexities while

implementing this in practical.

This technique depends on principle of Orthogonality. Orthogonality here

it means, it allows the sub carriers, which are orthogonal to each other, eliminating the

inter carrier interference between them and hence removes the cross talk.. This greatly

simplifies the design of both the transmitter and receiver, unlike conventional FDM; a

separate filter for each sub channel is not required.

This technique is a multi carrier modulation scheme which involves a lot

of sub carriers which are orthogonal to each other in which a single stream of data is split

into parallel streams each of which is coded and modulated on to a subcarrier.

Here every sub carrier is being modulated using the conventional phase

modulation like phase shift keying or quadrature amplitude modulation and this depends

upon the user requirement data rate.

In practice, OFDM signals are generated and detected using the Fast

Fourier Transform algorithm. OFDM has developed into a popular scheme for wideband

digital communication, wireless as well as copper wires.


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In OFDM, subcarriers overlap. They are orthogonal because the peak of

one subcarrier occurs when other subcarriers are at zero. This is achieved by realizing all

the subcarriers together using Inverse Fast Fourier Transform (IFFT). The demodulator at

the receiver parallel channels from an FFT block. Note that each subcarrier can still be

modulated independently.

Synchronization in frequency and time must be extremely good in

order to achieve a higher orthogonality between the sub carriers .Once this orthogonality

is lost we experience inter-carrier interference (ICI) that is the interference from one

subcarrier to another.

With the insertion of guard time with no transmission causes

problems for IFFT and FFT, which results in ICI. A delayed version of one subcarrier can

interfere with another subcarrier in the next symbol period. This is avoided by extending

the symbol into the guard period that precedes it. This is known as a cyclic prefix. It

ensures that delayed symbols will have integer number of cycles within the FFT

integration interval. This removes ICI so long as the delay spread is less than the guard

period.

Each sub-carrier is modulated with a conventional modulation

scheme (such as quadrature amplitude modulation) at a low symbol rate, maintaining data

rates similar to conventional single carrier modulation schemes in the same bandwidth.

Thus the high bit rates seen before on a single carrier is reduced to lower bit rates on the

subcarrier.


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In practice, OFDM signals are generated and detected using the Fast

Fourier Transform algorithm. OFDM has developed into a popular scheme for wideband

digital communication, wireless as well as copper wires.

Actually, FDM systems have been common for many decades.

However, in FDM, the carriers are all independent of each other. There is a guard period

in between them and no overlap whatsoever. This works well because in FDM system

each carrier carries data meant for a different user or application. FM radio is an FDM

system. FDM systems are not ideal for what we want for wideband systems. Using FDM

would waste too much bandwidth. This is where OFDM makes sense.

In OFDM, subcarriers overlap. They are orthogonal because the peak

of one subcarrier occurs when other subcarriers are at zero. This is achieved by realizing

all the subcarriers together using Inverse Fast Fourier Transform (IFFT). The

demodulator at the receiver parallel channels from an FFT block. Note that each

subcarrier can still be modulated independently.

Since orthogonality is important for OFDM systems,

synchronization in frequency and time must be extremely good. Once orthogonality is

lost we experience inter-carrier interference (ICI). This is the interference from one

subcarrier to another. There is another reason for ICI. Adding the guard time with no

transmission causes problems for IFFT and FFT, which results in ICI. A delayed version

of one subcarrier can interfere with another subcarrier in the next symbol period. This is

avoided by extending the symbol into the guard period that precedes it. This is known as

a cyclic prefix. It ensures that delayed symbols will have integer number of cycles within


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the FFT integration interval. This removes ICI so long as the delay spread is less than the

guard period.

BBaacckkggrroouunndd::

Most first generations systems were introduced in the mid 1980s, and can

be characterized by the use of analog transmission techniques and the use of simple

multiple access techniques such as Frequency Division Multiple Access (FDMA). First

generation telecommunications systems such as Advanced Mobile Phone Service

(AMPS) only provided voice communications. They also suffered from a low user

capacity, and security problems due to the simple radio interface used. Second generation

systems were introduced in the early 1990s, and all use digital technology. This provided

an increase in the user capacity of around three times. This was achieved by compressing

the voice waveforms before transmission.Third generation systems are an extension on the complexity of second-

generation systems and are expected to be introduced after the year 2000. The system

capacity is expected to be increased to over ten times original first generation systems.

This is going to be achieved by using complex multiple access techniques such as CodeDivision Multiple Access (CDMA), or an extension of TDMA, and by improving

flexibility of services available.

The telecommunications industry faces the problem of providing telephone

services to rural areas, where the customer base is small, but the cost of installing a wired

phone network is very high. One method of reducing the high infrastructure cost of a

wired system is to use a fixed wireless radio network. The problem with this is that for

rural and urban areas, large cell sizes are required to get sufficient coverage.

Fig.1.1 shows the evolution of current services and networks to the aim of

combining them into a unified third generation network. Many currently separate systems

and services such as radio paging, cordless telephony, satellite phones and private radio


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systems for companies etc, will be combined so that all these services will be provided by

third generation telecommunications systems.

Fig: 1.1 Evolution of current networks to the next generation of wireless networks.

Currently Global System for Mobile telecommunications (GSM) technology

is being applied to fixed wireless phone systems in rural areas. However, GSM uses time

division multiple access (TDMA), which has a high symbol rate leading to problems with

multipath causing inter-symbol interference. Several techniques are under consideration

for the next generation of digital phone systems, with the aim of improving cell capacity,multipath immunity, and flexibility. These include CDMA and OFDM. Both these

techniques could be applied to providing a fixed wireless system for rural areas.

However, each technique as different properties, making it more suited for specific

applications.

OFDM is currently being used in several new radio broadcast systems

including the proposal for high definition digital television (HDTV) and digital audio

broadcasting (DAB). However, little research has been done into the use of OFDM as a

transmission method for mobile telecommunications systems. In CDMA, all users

transmit in the same broad frequency band using specialized codes as a basis of

channelization. Both the base station and the mobile station know these codes, which are


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used to modulate the data sent. OFDM/COFDM allows many users to transmit in an

allocated band, by subdividing

the available bandwidth into many narrow bandwidth carriers. Each user is allocated

several carriers in which to transmit their data.

The transmission is generated in such a way that the carriers used are orthogonal

to one another, thus allowing them to be packed together much closer than standard

frequency division multiplexing (FDM). This leads to OFDM/COFDM providing a high

spectral efficiency.

Orthogonal Frequency Division Multiplexing is a scheme used in the area of

high-data-rate mobile wireless communications such as cellular phones, satellite

communications and digital audio broadcasting. This technique is mainly utilized tocombat inter-symbol interference.


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CHAPTER 3

NEED TO GO FOR STFC

FFoouurriieerr TTrraannssffoorrmm::

Back in the 1960s, the application of OFDM was not very practical. This was

because at that point, several banks of oscillators were needed to generate the carrier

frequencies necessary for sub-channel transmission. Since this proved to be difficult to

accomplish during that time period, the scheme was deemed as not feasible.

However, the advent of the Fourier Transform eliminated the initial complexity of

the OFDM scheme where the harmonically related frequencies generated by Fourier and

Inverse Fourier transforms are used to implement OFDM systems. The Fourier transform

is used in linear systems analysis, antenna studies, etc., The Fourier transform, in essence,

decomposes or separates a waveform or function into sinusoids of different frequencies

which sum to the original waveform. It identifies or distinguishes the different frequency

sinusoids and their respective amplitudes.

The Fourier transform off(x) is defined as:

dxexfFxj

)()(

and its inverse is denoted by:

deFxf xj)(2

1)(

(1)

(2)


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However, the digital age forced a change upon the traditional form of the Fourier

transform to encompass the discrete values that exist is all digital systems. The modified

series was called the Discrete Fourier Transform (DFT). The DFT of a discrete-time

system,x(n) is defined as:

1

0

2

)()(N

n

knN

j

enxk

1 kN

and its associated inverse is denoted by:

1

0

2

)(1

)(N

n

knN

j

ekN

nx

1 nN

However, in OFDM, another form of the DFT is used, called the Fast Fourier Transform

(FFT), which is a DFT algorithm developed in 1965. This new transform reduced the

number of computations from something on the order of

2N to .log2

2 NN

OOrrtthhooggoonnaalliittyy::

In geometry, orthogonal means, "involving right angles" (from Greek ortho,

meaning right, and gon meaning angled). The term has been extended to general use,

meaning the characteristic of being independent (relative to something else). It also can

mean: non-redundant, non-overlapping, or irrelevant. Orthogonality is defined for both

real and complex valued functions. The functions m(t) and n(t) are said to be

(3)

(4)

(5)


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orthogonal with respect to each other over the interval a < t < b if they satisfy the

condition:

b

amm dttt ,0)()(*

Where n m

OOFFDDMM CCaarrrriieerrss::

As fore mentioned, OFDM is a special form of MCM and the OFDM time

domain waveforms are chosen such that mutual orthogonality is ensured even though

sub-carrier spectra may over-lap. With respect to OFDM, it can be stated that

orthogonality is an implication of a definite and fixed relationship between all carriers in

the collection. It means that each carrier is positioned such that it occurs at the zero

energy frequency point of all other carriers.

OOrrtthhooggoonnaall FFrreeqquueennccyy DDiivviissiioonn MMuullttiipplleexxiinngg::

Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier

transmission technique, which divides the available spectrum into many carriers, each

one being modulated by a low rate data stream. OFDM is similar to FDMA in that the

multiple user access is achieved by subdividing the available bandwidth into multiple

channels that are then allocated to users. However, OFDM uses the spectrum much more

efficiently by spacing the channels much closer together. This is achieved by making all

the carriers orthogonal to one another, preventing interference between the closely spaced

carriers.

(6)


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In FDMA each user is typically allocated a single channel, which is used to

transmit all the user information. The bandwidth of each channel is typically 10 kHz-30

kHz for voice communications. However, the minimum required bandwidth for speech is

only 3 kHz. The allocated bandwidth is made wider then the minimum amount required

preventing channels from interfering with one another. This extra bandwidth is to allow

for signals from neighboring channels to be filtered out, and to allow for any drift in the

center frequency of the transmitter or receiver. In a typical system up to 50% of the total

spectrum is wasted due to the extra spacing between channels.

This problem becomes worse as the channel bandwidth becomes narrower, and

the frequency band increases. Most digital phone systems use vocoders to compress the

digitized speech. This allows for an increased system capacity due to a reduction in the

bandwidth required for each user. Current vocoders require a data rate somewhere

between 4- 13kbps, with depending on the quality of the sound and the type used. Thus

each user only requires a minimum bandwidth of somewhere between 2-7 kHz, using

QPSK modulation. However, simple FDMA does not handle such narrow bandwidths

very efficiently. TDMA partly overcomes this problem by using wider bandwidth

channels, which are used by several users. Multiple users access the same channel by

transmitting in their data in time slots. Thus, many low data rate users can be combined

together to transmit in a single channel, which has a bandwidth sufficient so that the

spectrum can be used efficiently.


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There are however, two main problems with TDMA. There is an overhead

associated with the change over between users due to time slotting on the channel. A

change over time must be allocated to allow for any tolerance in the start time of each

user, due to propagation delay variations and synchronization errors. This limits the

number of users that can be sent efficiently in each channel. In addition, the symbol rate

of each channel is high (as the channel handles the information from multiple users)

resulting in problems with multipath delay spread.

OFDM overcomes most of the problems with both FDMA and TDMA.

OFDM splits the available bandwidth into many narrow band channels (typically 100-

8000). The carriers for each channel are made orthogonal to one another, allowing them

to be spaced very close together, with no overhead as in the FDMA example. Because of

this there is no great need for users to be time multiplex as in TDMA, thus there is no

overhead associated with switching between users.

The orthogonality of the carriers means that each carrier has an integer

number of cycles over a symbol period. Due to this, the spectrum of each carrier has a

null at the center frequency of each of the other carriers in the system. This results in no

interference between the carriers, allowing then to be spaced as close as theoretically

possible. This overcomes the problem of overhead carrier spacing required in

FDMA.Each carrier in an OFDM signal has a very narrow bandwidth (i.e. 1 kHz), thus

the resulting symbol rate is low. This results in the signal having a high tolerance to

multipath delay spread, as the delay spread must be very long to cause significant ISI (e.g

> 500usec).


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OOFFDDMM ggeenneerraattiioonn::

To generate OFDM successfully the relationship between all the carriers must be

carefully controlled to maintain the orthogonality of the carriers. For this reason, OFDM

is generated by firstly choosing the spectrum required, based on the input data, and

modulation scheme used. Each carrier to be produced is assigned some data to transmit.

The required amplitude and phase of the carrier is then calculated based on the

modulation scheme (typically differential BPSK, QPSK, or QAM).

The required spectrum is then converted back to its time domain signal using an

Inverse Fourier Transform. In most applications, an Inverse Fast Fourier Transform

(IFFT) is used. The IFFT performs the transformation very efficiently, and provides a

simple way of ensuring the carrier signals produced are orthogonal.

The Fast Fourier Transform (FFT) transforms a cyclic time domain signal into its

equivalent frequency spectrum. This is done by finding the equivalent waveform,

generated by a sum of orthogonal sinusoidal components. The amplitude and phase of the

sinusoidal components represent the frequency spectrum of the time domain signal.

. The IFFT performs the reverse process, transforming a spectrum (amplitude and

phase of each component) into a time domain signal. An IFFT converts a number of

complex data points, of length, which is a power of 2, into the time domain signal of the

same number of points. Each data point in frequency spectrum used for an FFT or IFFT

is called a bin. The orthogonal carriers required for the OFDM signal can be easily


25/58

generated by setting the amplitude and phase of each bin, then performing the IFFT.

Since each bin of an IFFT corresponds to the amplitude and phase of a set of orthogonal

sinusoids, the reverse process guarantees that the carriers generated are orthogonal.

Fig. OFDM Block Diagram

Fig. above shows the setup for a basic OFDM transmitter and receiver. The signal

generated is a base band, thus the signal is filtered, then stepped up in frequency before

transmitting the signal. OFDM time domain waveforms are chosen such that mutual

orthogonality is ensured even though sub-carrier spectra may overlap. Typically QAM or

Differential Quadrature Phase Shift Keying (DQPSK) modulation schemes are applied to

the individual sub carriers. To prevent ISI, the individual blocks are separated by guard

intervals wherein the blocks are periodically extended.

For high data rate wideband wireless communications,

Orthogonal Frequency Division Multiplexing (OFDM) can be used with Multiple-Input

and Multiple-Output (MIMO) technology to achieve superior performance. In

conventional MIMO-OFDM systems, subcarrier based space processing was employed to

achieve optimal performance. However, it requires multiple discrete Fourier


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transform/inverse DFT (DFT/IDFT) blocks, each corresponding to one receive/ transmit

antenna. Even though DFT/IDFT can be efficiently implemented using fast Fourier

transform/inverse FFT (FFT/IFFT), its complexity is still a major concern for OFDM

implementation. In addition, the use of multiple antennas requires the base band signal

processing components to handle multiple input signals, thus inducing considerable

complexity for the decoder and the channel estimator at the receiver. To reduce the

complexity antennas, the schemes mentioned above, explicitly or implicitly, assume that

the channel state information (CSI) is known at the transmitter. In mobile

communications, where the channel can vary rapidly, it is difficult to maintain the CSI at

the transmitter up-to-date without substantial system overhead .Space-time-frequency

codes were proposed for OFDM systems to fully take advantage of the frequency

diversity and spatial diversity presented in frequency selective fading channels without

the requirement of the availability of CSI at the transmitter. For such a system, traditional

subcarrier based space processing induces considerable complexity due to the reasons

mentioned before. In this paper, we propose to use pre-DFT processing to reduce the

receiver complexity of MIMO-OFDM systems with space-time-frequency coding. In our

proposed scheme, the received signals at the receiver are first weighted and then

combined before the DFT processing. Owing to the pre-DFT processing, the number of

DFT blocks required at the receiver can be reduced, and a high dimensional MIMO

system can be shrunk into an equivalently low dimension one. Both enable effective

complexity reduction one important issue in the proposed pre-DFT processing scheme for

MIMO-OFDM systems with space-time-frequency coding is the calculation of the

weighting coefficients before the DFT processing. In general, the weighting coefficients


27/58

Calculation are specific to the space-time-frequency coding scheme. In this paper, we

propose a universal weighting coefficients calculation algorithm that can be applied in

most practical space-time-frequency codes such as those proposed. This makes the design

of the pre-DFT processing scheme independent of the optimization of the space-time-

frequency coding, which is desirable for multiplatform systems. In general, the weighting

coefficients before the DFT processing can be calculated assuming that the CSIs are

explicitly available. In this paper, we will show that the weighting coefficients can also

be obtained using the signal space method without the explicit knowledge of the CSIs.

This helps to reduce the complexity of channel estimation required by the space-time-

frequency decoding since the number of equivalent channel branches required to be

estimated in the proposed scheme can be reduced from the number of receive antennas to

the number of DFT blocks.


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SYSTEM MODEL

We investigate a MIMO-OFDM system with N subcarriers as shown

in Fig. 1. In the system, there are F transmitting antennas and M receives antennas. At the

tithe OFDM symbol Period, the output of the space-time-frequency encoder is assumed

to be as follows:

Where c (t) n, f is the coded information symbol at the nth subcarrier of the t th OFDM

symbol period transmitted from the fth transmit antenna, and T is the number of OFDM

symbols in a space-time-frequency codeword. When T = 1, the space-time- frequency

code reduces to a space-frequency code. After the IDFT processing, at the t th OFDM

symbol period, the l th sample at the f th transmit antenna is given by where denotes the

convolution product, h(m,f) l denotes the CIR between the fth transmit antenna and the


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Mth

receive antenna, and z(m) t,l denotes the additive white Gaussian noise (AWGN)

component at the mth receive antenna. At the receiver, before the DFT processing, theM

data streams from the output of the Mreceive antennas are weighted and then combined

to form Q branches. After the guard interval removal, the weighted and combined signals

are then applied to the DFT processors. Note that there are Q branches, and hence the

number of DFT blocks required at the receiver is Q. As a result, compared to the

conventional receiver structure, where M DFT blocks are used, the number of DFT

blocks employed at the receiver can be reduced when pre-DFT processing is used. For

the qth branch, the output of the DFT processor at the tth OFDM symbol period is given

by

and m,q is the weighting coefficient for the mth receive antenna at the qth branch. In

order to keep the noise white and its variance at different branch the same, we assume

that the weighting coefficients are normalized (i.e.,H = IQ,) where is an M Q

matrix with the (m, q)th entry given by m,q, and IQ is a Q Q identify matrix).


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WEIGHTING COEFFICIENTS CALCULATION WITH EXPLICIT CSI

In this section, we will present a way to calculate the weighting

coefficients for the proposed pre-DFT processing scheme. When the ML decoder is

employed, the pair-wise error probability (PEP) can be used to denote system

performance, which is further determined by the pair-wise codeword distance.The pair-

wise codeword distance d2(C,E|H) between a favored coded sequence


31/58


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Minimizing the pair-wise error probability is equivalent to maximizing the pair-wise

codeword distance given, a close observation of above equation indicates that the optimal

weighting coefficients are related to the specific codeword pair. To make the weighting

coefficients and the codeword pair independent, we average (7) over all codewords pair

ensemble

where the overbar stands for the average over all the codewords pair ensemble. In order

to rewrite above equation into a matrix form, let Cn be an F Tmatrix with the (f, t)th

entry given by c(t) n,f, En be an matrix with the (f, t)th entry given by e(t) n,f, and Hn (n

= 0, ,N 1) be anMFmatrix with the (m, f)th entry given byH(m,f) n . With these

definitions, (8) can be written into


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Let the eigenvalues of be q (q = 1, ,M) with 1 2 M and

q (q = 1, ,Q) be the ith column of. It is well known that when q (q = 1, ,Q)

are

the conjugate of the eigenvectors of corresponding to the eigenvalues q (q = 1,

,M), the maximum C,E|H) is achieved and is given by

In general, to obtain in (14), we need both knowledge of the CSIs and the space-time-

frequency code since kn is dependent on the specific space-time-frequency code.

However, since the channel information is not available at the transmitter, the space time-

frequency coding scheme should not favor or bias a particular sub-carrier or a particular

transmit antenna. As a result, in the following, it will be shown that for most practical

space-time-frequency codes, it is reasonable to assume that is in the following form:


34/58

where k is a constant that is independent of n. As a result, the weighting coefficients

( which are the conjugate of the eigenvectors of , are

independent of the specific space-time-frequency coding scheme.

For the space-time-frequency codes proposed for example, as shown in Appendix kn

can be expressed as follows

where k1 is a constant number independent ofn, (n) =[0, -----, 0, 1, 0,-------, 0] is an

F dimensional standard basis vector with 1 in its (n)th component and 0 elsewhere,

and (n) is determined by the space-frequency coding scheme. Using (14), as shown in

Appendix A, can be proved to be in the form of below equation with k= k1/F.For

space-time-frequency codes where the orthogonal space time block code (STBC) is

employed as an inner code. Using the orthogonal property of STBC, we can easily prove

that

It is reasonable to assume that the signals at the input of the inner encoder have the same

distribution for different subcarriers and different transmit antennas, especially when an

Interleaver is employed between the outer encoder and thinner encoder. As a result, kn

can be written as

kn = kIF .


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Therefore, (10) can also be simplified into above equation for these codes. For a general

space-time-frequency code such as that proposed, simulation results show that excellent

performance can be achieved by using the weighting coefficients calculated based on .

WEIGHTING COEFFICIENTS CALCULATION WITHOUT EXPLICIT CSI:

In the following, we propose a way to obtain the weighting coefficients (i.e., the

eigenvectors of ) without explicit CSI. This is especially important for differential

modulation, where the CSI is not supposed to be explicitly known at the receiver. For

coherent modulation, when CSI is not explicitly required for the weighting coefficients

calculation, the complexity of channel estimation2 can be reduced since the number of

equivalent channel branches required to be estimated is now reduced from the number of

receive antennas to the number of DFT branches.

Note that the covariance matrix of the received signal vector

can be given by


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Similar to the SIMO case proposed in [10], when a large number of subcarriers are used,

it is reasonable to assume that the transmitted signals are white, that is

whereEs is the average energy of the coded symbol. Hence, by substituting (19) into (18)

and after some manipulations,m,m_ can be proven to be given by

whereN0 is the variance of the noise. Using (13), we then have

where m,m_ is the (m,m_)th

entry of . From (21), it can be easily seen that the

eigenvectors of are the same as those of R. As a result, we can obtain the weighting

coefficients directly from R without explicit knowledge of CSI. weighting and

combining, weighting coefficients calculation, DFT-processing, channel estimation, and

ML decoding. By weighting and combining before the DFT processing, the number of

branches to be handled by the ML decoder is reduced from Mto Q. As a result, compared

with the subcarrier based processing, the complexity of ML decoding can be reduced. As

for the complexity coming from the DFT processing3, the pre-DFT weighting and

combining, the ratio of the number of multiplications needed between the proposed

scheme and the subcarrier based scheme is as follows:


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From (22), it can be seen that, when log2N >> M, is close to Q/M. From (12), it is easy

to see that the number of DFT blocks at the receiver, Q, is determined by the rank of.

After some manipulations, we have

Where

l are the receive correlation matrix as defined in [19]. From (23), we can see that is

singular when R1/2 is not of full row rank or FL is smaller than M. In this case, the

number of DFT blocks required can be smaller than the number of receive antennas to

achieve optimal performance. On the other hand, when is nonsingular, it is still

possible to achieve good performance with a limit number of DFT blocks due to the

small contribution of the small eigen value to the average pair-wise codeword distance


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VI. SIMULATION RESULTS:-

In the considered MIMO-OFDM system, the number of subcarriers in an OFDM symbol

is 64 (N= 64) and the length of the guard interval is 12 (Ng = 12). In the simulations, we

assume that there are four receive antennas at the receiver and two or four transmit

antennas at the transmitter. Further, we assume that the channel is quasi-static and perfect

channel information is available at the receiver. Without special notation, the optimal

lines in the figures are obtained using ML decoders based on subcarrier space processing

as the corresponding references. Further, Eb/N0 in all figures is a short hand for Eb/N0

per receive antenna.

A. Performance of space-time-frequency codes proposed in with pre-DFT

processing:-

In this part, we consider the code proposed, where full diversity order provided by the

fading channel can be achieved with low trellis complexity. As we use the optimal rate

2/3 TCM codes designed for flat fading channels. For simplicity, only the 4-state 8PSK

TCM code is used and the parity check matrix is (6 4 7) in octal form. When the two-ray

equal gain Rayleigh fading channel model is employed, the bit error rate (BER)

performance of the proposed scheme is shown in Fig above.[main STFC block diagram

of proposal] It can be observed that, with the increase of the number of DFT blocks at the

receiver, better performance can be achieved. When the number of DFT blocks is

increased from one to two, significant performance gain (e.g., 5.01 dB when Pe = 104)

can be achieved. When the number of DFT blocks is three or four, the performance is

close to optimal. When the weighting coefficients are obtained based on the signal space


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method as discussed in Section IV, the performance of the proposed scheme over two-ray

equal gain Rayleigh fading channel is also shown in Fig. 2. In the simulations, P is set to

64. From Fig proposal we can see that the performance of the proposed scheme using the

signal space method is almost the same as that with complete CSI.

B. Performance of space-time-frequency codes proposed in [8] and [6] with pre-DFT

processing

The space-time-frequency code proposal can achieve full diversity without any rate

reduction. In our simulations, the codeword of the space-frequency code C .And QRD-M

algorithm is employed as the space-time-frequency decoder. The performance of the

proposed scheme over a six-ray exponential decay quasi static Rayleigh fading channel

The general space-time-frequency code proposed is employed with 16-state trellis and

QPSK modulation. It can be seen from Fig of OFDM that similar results can be obtained

as those in Part A irrespective for channel type and system configuration. As a result, the

weighting coefficients obtained can also be applied here.


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RESULTS

CONCLUSION:-

In this project, a pre-DFT processing scheme was proposed for a MIMO-OFDM system

with space-time-frequency coding. With the proposed scheme, system complexity and

performance can be effectively traded off. A simple weighting coefficients calculation

algorithm was also derived. Theoretical analysis and simulation results have shown that

the algorithm can be applied for most existing practical space time- frequency codes.


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Using the proposed scheme, we have also shown that it is possible to use a very limited

number of DFT blocks to achieve near optimal system performance.

In general, to obtain , we need both knowledge of the CSIs and the space-time-

frequency code since kn is dependent on the specific space-time-frequency code.

However, since the channel information is not available at the transmitter, the space time-

frequency coding scheme should not favor or bias a particular sub-carrier or a particular

transmit antenna. As a result, in the following, it will be shown that for most practical

Space-time-frequency codes, it is reasonable to assume that


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AAppppeennddiixx

DDaattaa CCoolllleeccttiioonn

MMoodduullaattiioonn TTeecchhnniiqquueess::

QQuuaaddrraattuurree AAmmpplliittuuddee MMoodduullaattiioonn ((QQAAMM))::

This modulation scheme is also called quadrature carrier multiplexing. Infact, this

modulation scheme enables to DSB-SC modulated signals to occupy the same

transmission BW at the receiver o/p. it is, therefore, known as a bandwidth-conservation

scheme. The QAM Tx consists of two separate balanced modulators, which are supplied,

with two carrier waves of the same freq but differing in phase by 90. The o/p of the two

balanced modulators are added in the adder and transmitted.

Fig. QAM System

The transmitted signal is thus given by

S (t) = X1 (t) A cos (2Fc t) + X2 (t) A sin (2Fc t)

Hence, the multiplexed signal consists of the in-phase component A X1 (t) and

the quadrature phase component A X2 (t).


43/58

BBaallaanncceedd MMoodduullaattoorr::

A DSB-SC signal is basically the product of the modulating or base band signal

and the carrier signal. Unfortunately, a single electronic device cannot generate a DSB-

SC signal. A circuit is needed to achieve the generation of a DSB-SC signal is called

product modulator i.e., Balanced Modulator.

We know that a non-linear resistance or a non-linear device may be used to

produce AM i.e., one carrier and two sidebands. However, a DSB-SC signal contains

only 2 sidebands. Thus, if 2 non-linear devices such as diodes, transistors etc., are

connected in balanced mode so as to suppress the carriers of each other, then only

sidebands are left, i.e., a DSB-SC signal is generated. Therefore, a balanced modulator

may be defined as a circuit in which two non-linear devices are connected in a balanced

mode to produce a DSB-SC signal.

QQuuaaddrraattuurree PPhhaassee SShhiifftt KKeeyyiinngg ((QQPPSSKK)) ::

In communication systems, we have two main resources. These are:

1. Transmission Power2. Channel bandwidth

If two or more bits are combined in some symbols, then the signaling rate will be

reduced. Thus, the frequency of the carrier needed is also reduced. This reduces the

transmission channel B.W. Hence, because of grouping of bits in symbols; the

transmission channel B.W can be reduced. In QPSK two successive bits in the data

sequence are grouped together. This reduces the bits rate or signaling rate and thus

reduces the B.W of the channel. In case of BPSK, we know that when sym. Changes the


44/58

level, the phase of the carrier is changed by 180. Because, there were only two syms in

BPSK, the phase shift occurs in 2 levels only. However, in QPSK, 2 successive bits are

combined. Infact, this combination of two bits forms 4 distinct syms. When the sym is

changed to next sym, then the phase of the carrier is changed by 45 degrees.

S.No I/p successive bits symbol phase shift in carrier

I=1 1(1v) 0(-1v) S1 /4

I=2 0(-1v) 0(-1v) S2 3/4

I=3 0(-1v) 1(1v) S3 5/4

I=4 1(1v) 1(1v) S4 7/4

GGeenneerraattiioonn ooffQQPPSSKK::

Here the i/p binary seq. is first converted into a bipolar NRZ type of signal. This

signal is denoted by b (t). It represents binary 1by +1V and binary 0 by -1V. The

demultiplexer divides b (t) into 2 separate bit streams of the odd numbered and even

numbered bits. Here Be (t) represents even numbered sequence and Bo (t) represents odd

numbered sequence. The symbol duration of both of these odd numbered sequences is

2Tb. Hence, each symbol consists of 2 bits.

Fig. Generation of QPSK

It may be observed that the first even bit occurs after the first odd bit. Hence, even

numbered bit sequence Be (t) starts with the delay of one bit period due to first odd bit.


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Thus, first symbol of Be (t) is delayed by one bit period due to first odd bit. Thus, first

symbol of Be (t) is delayed by on bit period Tb with respect to first symbol of Bo (t).

This delay of Tb is known as offset. This shows that the change in the levels of Be (t) and

Bo (t) cant occur at the same time due to offset or staggering. The bit stream Be (t)

modulates carrier cosine carrier and B0(t) modulates sinusoidal carrier. These modulators

are the balanced modulators. The 2 carriers are Ps.cos (2Fc.t) and Ps.sin (2Fc.t)

have been shown in fig. Their carriers are known as quadrature carriers. Due to the

offset, the phase shift in QPSK signal is /2.

FFFFTT && IIFFFFTT::

In practice, OFDM systems are implemented using a combination of FFT and

IFFT blocks that are mathematically equivalent versions of the DFT and IDFT,

respectively, but more efficient to implement.

An OFDM system treats the source symbols (e.g., the QPSK or QAM symbols

that would be present in a single carrier system) at the Tx as though they are in the freq-

domain. These syms are used as the i/ps to an IFFT block that brings the sig into the

time domain. The IFFT takes in N syms at a time where N is the num of sub carriers in

the system. Each of these N i/p syms has a symbol period of T secs. Recall that the basis

functions for an IFFT are N orthogonal sinusoids. These sinusoids each have a different

freq and the lowest freq is DC. Each i/p symbol acts like a complex weight for the

corresponding sinusoidal basis fun. Since the i/p syms are complex, the value of the sym

determines both the amplitude and phase of the sinusoid for that sub carrier.


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The IFFT o/p is the summation of all N sinusoids. Thus, the IFFT block provides

a simple way to modulate data onto N orthogonal sub carriers. The block of N o/p

samples from the IFFT make up a single OFDM sym. The length of the OFDM symbol is

NT where T is the IFFT i/p symbol period mentioned above.

Fig. FFT & IFFT diagram

After some additional processing, the time-domain sig that results from the IFFT

is transmitted across the channel. At the Rx, an FFT block is used to process the received

signal and bring it into the freq domain. Ideally, the FFT o/p will be the original syms

that were sent to the IFFT at the Tx. When plotted in the complex plane, the FFT o/p

samples will form a constellation, such as 16-QAM. However, there is no notion of a

constellation for the time-domain sig. When plotted on the complex plane, the time-

domain sig forms a scatter plot with no regular shape. Thus, any Rx processing that uses

the concept of a constellation (such as symbol slicing) must occur in the frequency-

domain.

AAddddiinngg aa GGuuaarrdd PPeerriioodd ttoo OOFFDDMM::

One of the most important properties of OFDM transmissions is the robustness

against multipath delay spread. This is achieved by having a long symbol period, which

minimizes the ISI. The level of robustness, can infact is increased even more by the

addition of a guard period b/w transmitted syms. The guard period allows time for


47/58

multipath sigs from the pervious symbol to die away before the information from the

current symbol is gathered.

The most effective guard period to use is a cyclic extension of the symbol. If a

mirror in time, of the end of the symbol waveform is put at the start of the symbol as the

guard period, this effectively extends the length of the symbol, while maintaining the

orthogonally of the waveform. Using this cyclic extended symbol the samples required

for performing the FFT (to decode the sym), can be taken anywhere over the length of the

sym. This provides multipath immunity as well as sym time synchronization tolerance.

As long as the multipath delay echos stay within the guard period duration, there

is strictly no limitation regarding the signal level of the echos: they may even exceed the

signal level of the shorter path! The signal energy from all paths just adds at the input to

the receiver, and since the FFT is energy conservative, the whole available power feeds

the decoder.

If the delay spread is longer then the guard interval then they begins to cause ISI.

However, provided the echos are sufficiently small they do not cause significant

problems. This is true most of the time as multipath echos delayed longer than the guard

period will have been reflected of very distant objects. Other variations of guard periods

are possible. One possible variation is to have half the guard period a cyclic extension of

the symbol, as above, and the other half a zero amplitude signal.


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Using this method the symbols can be easily identified. This possibly allows for

symbol timing to be recovered from the signal, simply by applying envelop detection.

The disadvantage of using this guard period method is that the zero period does not give

any multipath tolerance, thus the effective active guard period is halved in length. It is

interesting to note that this guard period method has not been mentioned in any of the

research papers read, and it is still not clear whether symbol timing needs to be recovered

using this method.

CHANNEL CHARACTERISTICS

Propagation Characteristics of mobile radio channels:

In an ideal radio channel, the received signal would consist of only a single direct

path signal, which would be a perfect reconstruction of the transmitted signal. However

in a real channel, the signal is modified during transmission in the channel.

It is known that the performance of any wireless systems performance is affected

by the medium of propagation, namely the characteristics of the channel. In

telecommunications in general, a channel is a separate path through which signals can

flow. In the ideal situation, a direct line of sight between the transmitter and receiver is

desired. But alas, it is not a perfect world; hence it is imperative to understand what goes

on in the channel so that the original signal can be reconstructed with the least number of

errors.

The received signal consists of a combination of attenuated, reflected, refracted,

and diffracted replicas of the transmitted signal. On top of all this, the channel adds noise

to the signal and can cause a shift in the carrier frequency if the transmitter, or receiver is


49/58

moving (Doppler effect). Understanding of these effects on the signal is important

because the performance of a radio system is dependent on the radio channel

characteristics.

AAtttteennuuaattiioonn::

Attenuationis the drop in the signal power when transmitting from one point to

another. It can be caused by the transmission path length, obstructions in the signal path,

and multipath effects. Fig.3.1 shows some of the radio propagation effects that cause

attenuation. Any objects, which obstruct the line of sight signal from the transmitter to

the receiver, can cause attenuation.

Fig. Some channel characteristics

Shadowing of the signal can occur whenever there is an obstruction between the

transmitter and receiver. It is generally caused by buildings and hills, and is the most

important environmental attenuation factor. Shadowing is most severe in heavily built up

areas, due to the shadowing from buildings. However, hills can cause a large problem due

to the large shadow they produce.


50/58

Radio signals diffract off the boundaries of obstructions, thus preventing total

shadowing of the signals behind hills and buildings. However, the amount of diffraction

is dependent on the radio frequency used, with low frequencies diffracting more then

high frequency signals. Thus high frequency signals, especially, Ultra High Frequencies

(UHF), and microwave signals require line of sight for adequate signal strength. To over

come the problem of shadowing, transmitters are usually elevated as high as possible to

minimize the number of obstructions

MMuullttiippaatthh EEffffeeccttss::

RRaayylleeiigghh ffaaddiinngg::

In a radio link, the RF signal from the transmitter may be reflected from objects

such as hills, buildings, or vehicles. This gives rise to multiple transmission paths at the

receiver. Fig. 3.2 show some of the possible ways in which multipath signals can occur.

Fig. Multipath Signals

The relative phase of multiple reflected sigs can cause constructive or destructive

interference at the Rx. This is experienced over very short distances (typically at half


51/58

wavelength distances), thus is given the term fast fading. These variations can vary from

10-30dB over a short distance.

The Rayleigh distribution is commonly used to describe the statistical time

varying nature of the received signal power. It describes the probability of the signal

level. being received due to fading.

Frequency Selective Fading:

In any radio transmission, the channel spectral response is not flat. It has dips or

fades in the response due to reflections causing cancellation of certain frequencies at the

receiver. Reflections off near-by objects (e.g. ground, buildings, trees, etc) can lead to

multipath signals of similar signal power as the direct signal. This can result in deep nulls

in the received signal power due to destructive interference. For narrow bandwidth

transmissions if the null in the frequency response occurs at the transmission frequency

then the entire signal can be lost. This can be partly overcome in two ways.

By transmitting a wide bandwidth signal or spread spectrum as CDMA, any dips

in the spectrum only result in a small loss of signal power, rather than a complete loss.

Another method is to split the transmission up into many small bandwidth carriers, as is

done in a COFDM/OFDM transmission. The original signal is spread over a wide

bandwidth thus; any nulls in the spectrum are unlikely to occur at all of the carrier

frequencies. This will result in only some of the carriers being lost, rather then the entire

signal. The information in the lost carriers can be recovered provided enough forward

error corrections are sent.


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Delay Spread:

The received radio signal from a transmitter consists of typically a direct signal,

plus reflections of object such as buildings, mountings, and other structures. The reflected

signals arrive at a later time than the direct signal because of the extra path length, giving

rise to a slightly different arrival time of the transmitted pulse, thus spreading the

received energy. Delay spreadis the time spread between the arrival of the first and last

multipath signal seen by the receiver.

In a digital system, the delay spread can lead to inter-symbol interference. This is

due to the delayed multipath signal overlapping with the following symbols. This can

cause significant errors in high bit rate systems, especially when using time division

multiplexing (TDMA). Fig.3.4 shows the effect of inter-symbol interference due to delay

spread on the received signal. As the transmitted bit rate is increased the amount of inter-

symbol interference also increases. The effect starts to become very significant when the

delay spread is greater then ~50% of the bit time.

Fig. Multi delay spread


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shows the typical delay spread that can occur in various environments.

Doppler Shift:

When a wave source and a receiver are moving relative to one another the

frequency of the received signal will not be the same as the source. When they are

moving toward each other the frequency of the received signal is higher then the source,

and when they are approaching each other the frequency decreases. This is called the

Doppler Effect.An example of this is the change of pitch in a cars horn as it approaches

then passes by. This effect becomes important when developing mobile radio systems.

The amount the frequency changes due to the Doppler effect depends on the relative

motion between the source and receiver and on the speed of propagation of the wave. The

Doppler shift in frequency can be written:

Where fis the change in frequency of the source seen at the receiver, fo is the frequency

of the source, v is the speed difference between the source and transmitter, and c is the

speed of light.

For example: Letfo = 1GHz, and v = 60km/hr (16.7m/s) then the Doppler shift will

be:

This shift of 55Hz in the carrier will generally not effect the transmission. However,

Doppler shift can cause significant problems if the transmission technique is sensitive to

carrier frequency offsets (for example COFDM) or the relative speed is higher (for

example in low earth orbiting satellites).


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Inter Symbol Interference:

As communication systems evolve, the need for high symbol rates becomes more

apparent. However, current multiple access with high symbol rates encounter several

multi path problems, which leads to ISI. An echo is a copy of the original signal delayed

in time. ISI takes place when echoes on different-length propagation paths result in

overlapping received symbols. Problems can occur when one OFDM symbol overlaps

with the next one. There is no correlation between two consecutive OFDM symbols and

therefore interference from one symbol with the other will result in a disturbed signal

In addition, the symbol rate of communications systems is practically

limited by the channels bandwidth. For the higher symbol rates, the effects of ISI must

be dealt with seriously. Several channel equalization techniques can be used to suppress

the ISIs caused by the channel. However, to do this, the CIR channel impulse response,

must be estimated.

Recently, OFDM has been used to transmit data over a multi-path

channel. Instead of trying to cancel the effects of the channels ISIs, a set of sub-carriers

can be used to transmit information symbols in parallel sub-channels over the channel,

where the systems output will be the sum of all the parallel channels throughputs.

This is the basis of how OFDM works. By transmitting in parallel

over a set of sub-carriers, the data rate per sub-channel is only a fraction of the data rate

of a conventional single carrier system having the same output. Hence, a system can be

designed to support high data rates while deferring the need for channel equalizations.


55/58

In addition, once the incoming signal is split into the respective transmission sub-

carriers, a guard interval is added between each symbol. Each symbol consists of useful

symbol duration, Ts and a guard interval, t, in which, part of the time, a signal of Ts is

cyclically repeated.

AWGN channel

For the Additional White Gaussian Noise (AWGN) channel the received signal is equal

to the transmitted signal with some portion of white Gaussian white noise added. This

channel is particularly important for discrete models operating on a restricted number

space, because this allows one to optimise the circuits in terms of their noise

performance. The block diagram of the AWGN channel is given in the next figure.

s(t) = s(t) + n(t)

where n(t) is a sample function of a Gaussian random process. This represents white

Gaussian noise.

Multi path channel

The multipath channel is the last of the static channels. It reflects the fact that

electromagnetic waves can travel over various paths from the transmission antenna to the

receiver antenna. The receiver antenna sums up all the different signals. Therefore, the

mathematical model of the multipath environment creates the received transmission

signal by summing up scaled and delayed versions of the original transmission signal.

This superposition of signals causes ISI.

The following figure shows a multipath environment.


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The mathematical model follows as:

Fading channels

Fading channels represent a mathematical model for wireless data exchange in a physical

environment which changes over time. These changes arise for two reasons:

1. The environment is changing even though the transmitter and receiver are fixed;examples are changes in the ionosphere, movement of foliage and movement of

reflectors and scatterers.

2. Transmitter and receiver are mobile even though the environment might be static.3. The next figure shows a multipath fading environment. The fading is modeled by

the fact that the environment is changing.

The block diagram, shown in the next figure, details a DSP model for the multipathenvironment

Mathematically the DSP model can be formulated as follows:

DSP model and mathematical description are close to the underlying physical

phenomena. This makes them unsuitable for practical channel models. To establish


57/58

practical channel models we employ statistical methods to abstract and generalize the

fading channel models. In the following two subsections we discuss Rayleigh and Rician

fading channels. Both represent statistical channel modes, the difference between them is

that the Rayleigh model does not assume a direct or prominent path and the Ricien model

assumes a direct path. The last channel model extends the ideas of Rayleigh and Rician

fading channels with mobility aspects. The resulting mobile fading channels model the

degrading effects in the frequency domain of wireless multipath channels.

.

OFDM Applications:

DAB HDTV ADSL & HDSL WLANs (IEEE 802.11 & Hiper LAN II


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BBiibblliiooggrraapphhyy::

Space time coded OFDM for higher data rates wireless communication overwideband channels by Dakshi agarwal ,vahid tarokh

Full rate diversity space frequency codes with optimum coding advantage byweifeng su,zoftan safar IEEE -2006

Introduction to space time frequency codes by sumeet sandhuand rohit ranbar Bahai, A., and B. Saltzberg. Multicarrier Digital Communications: Theory and

Applications of OFDM. New York: Kluwer Academic/Plenum Publishers, 1999

Van Nee, R., and R. Prasad. OFDM Wireless Multimedia Communications.Boston: Artech House, 2000

Couch II, L. W. Digital and Analog Communication Systems. New Jersey:Prentice-Hall, 1997

Keller, T., and L. Hanzo. Adaptive Multicarrier Modulation: A ConvenientFramework for Time-Frequency Processing in Wireless Communications.

Proceedings of the IEEE 88.5 (2000) 609 - 639

OFDM Wireless Technology, Eric Lawrey and Craig Blackburn. 2000. JamesCook University. < http://www.eng.jcu.edu.au/eric/thesis/Thesis.htm >.

Spread Spectrum Scene, SSS Online, Inc. 2001 < http://sss-mag.com/index.html OFDM Receiver for Broadband Receivers, Michael Speth. Institute for Integrated

Signal Processing Systems. 2001. < http://www.ert.rwth-aachen.de/index_e.htm >.
http://www.eng.jcu.edu.au/eric/thesis/Thesis.htmhttp://sss-mag.com/index.htmlhttp://www.ert.rwth-aachen.de/index_e.htmhttp://www.ert.rwth-aachen.de/index_e.htmhttp://sss-mag.com/index.htmlhttp://www.eng.jcu.edu.au/eric/thesis/Thesis.htm

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