Performance Evaluation of OFDM System for Different Channel and Different
Modulation Techniques
Thesis Report
Department of Electronic and Telecommunication Engineering (ETE)

Submitted By
Foysal Bin Wadud (T-093011)
Gazi Shamsul Arefeen Shams (T-093016)

Supervised By
Engr. Mohammad Jashim Uddin

Contact Information:
Foysal Bin Wadud (Mamun),
Dept. of ETE,
International Islamic University Chittagong,
Metric No.: T093011,
Email: mamunmoon19@yahoo.com
Contact No.: +8801717934676

Gazi Shamsul Arefeen (Shams)
Dept. of ETE,
International Islamic University Chittagong,
Metric No.: T093016,
Email: shams.ete@gmail.com
Contact No.: +8801676848247

Contact Information of Supervisor:
Md. Jashim Uddin
Dept. Of ETE,
International Islamic University Chittagong.
Contact No. +8801716-823959
Email: jashimcuet@yahoo.com

Abstract

The demand for high-speed mobile wireless communications is rapidly growing. Orthogonal
Frequency Division Multiplexing (OFDM) technology promises to be a key technique for achieving the high data capacity and spectral efficiency requirements for wireless communication systems in the near future. An Orthogonal Frequency Division Multiplexing
(OFDM) scheme offers high spectral efficiency and better resistance to fading environments. In
OFDM the data is modulated using multiple numbers of sub-carriers that are orthogonal to each other because of which the problems associated with other modulation schemes such as Inter
Symbol Interference (ISI) and Inter Carrier Interference (ICI) is reduced. This paper deals with the analysis of OFDM System utilizing different modulation techniques over Rayleigh, Rician and Additive White Gaussian Noise (AWGN) fading environments with the use of pilot aided arrangement and finally the results are conveyed.
The aim of this thesis is to provide practical solutions for OFDM communication system by showing its better performance on different channel using different modulation technique. We applied different channel like AWGN, Rayleigh and Rician over OFDM system. We analyzed the performance of OFDM system regarding different channel. We analyzed the performance and showed the most suitable channel for OFDM communication system.
Moreover, we also applied different modulation scheme over OFDM system to show which modulation technique is more efficient for OFDM system. Here we used BPSK, QPSK, 16-QAM and 64-QAM modulation technique.
From our experiment we found that, among AWGN & the fading channels (Rayleigh & Rician),
AWGN channel has less BER and P(e) than others. So we can say that, for OFDM system,
AWGN channel is most suitable.
We also found that, in all environments BPSK shows better performance than QPSK, 16QAM &
64QAM. When modulation level increased, corresponding BER & P(e) also increased.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

I

Acknowledgements

First of all, for our achievement we would like to thank to almighty Allah as this work was not possible if Allah was not with us.
We would like to thank our thesis supervisor Engr. Mohammad Jashim Uddin for his kind and helpful guidance during the duration of the thesis. His dedication and depth of knowledge truly inspired us during the work. We would also like to express our gratitude towards him for providing us with all the useful links and books which proved really helpful during our analysis.
We would like to thank the all teachers of the Department of Electronic and Telecommunication
Engineering for their friendship and helpful discussions. Many of the ideas discussed in this thesis come from the collaborations with the teachers.
Last but not least, we would like to thank our family for their love and encouragement.

Research Team
Foysal Bin Wadud
Gazi Shamsul Arefeen
Department of ETE
International Islamic University Chittagong

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

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TABLE OF CONTENTS
Abstract…………………………………………………………………………………...

I

Acknowledgements………………………………………………………………………

II

Table of Contents………………………………………………………………………...

III-V

List of figures…………………………………………………………………………….

VI

List of tables……………………………………………………………………………...

VIII

Acronyms………………………………………………………………………………...

IX-X

CHAPTER

INTRODUCTION……………………………………………..

1-5

1.1

Objectives………………………………………………………

1

1.2

Background …………………………………………………….

2

1.3

Aim & objective………………………………………………..

4

1.4
CHAPTER

1

Paper outline……………………………………………………

4

2

ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING

6-15

2.1

Basic principles of OFDM……………………………………...

6

2.2

Theory of OFDM……………………………………………….

7

2.3

OFDM system model…………………………………………..

10

2.4

Advantages and Disadvantages of OFDM……………………..

12

2.5

Applications of OFDM…………………………………………

13

2.5.1

Digital Audio Broadcasting (DAB)…………………………….

13

2.5.2

Higher Definition Television (HDTV)………………………....

14

2.6

Challenges of OFDM…………………………………………..

15

2.6.1

Peak Average Power Ratio…………………………………….

15

2.6.2

Mobility………………………………………………………...

15

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

III

CONTENTS
CHAPTER

3

LITERATURE SURVEY…………………………………………

16-32

3.1

Rayleigh fading……………………………………………….

16

3.1.2

Rician fading………………………………………………….

19

3.1.3

AWGN channel………………………………………………

21

3.2

Modulation Scenario………………………………………….

22

3.2.1

Binary Phase Shift keying (BPSK)…………………………...

23

3.2.2

Quadrature Phase Shift Keying (QPSK)……………………..

26

3.2.3

Quadrature Amplitude Modulation (QAM)………………….

28

3.3

QAM noise margin…………………………………………...

31

3.4

QAM Applications…………………………………………..

32

4

METHODOLOGY………………………………………….

33-44

4.1

Pre-thesis Work………………………………………………

33

4.2

Work Done at Thesis…………………………………………

35

4.3

Simulation Procedure………………………………………...

37

4.4

Simulation Basis……………………………………………..

38

4.5

Simulation Model…………………………………………….

43

4.6
CHAPTER

16

3.1.1

CHAPTER

Channel Environment………………………………………...

System Parameters…………………………………………...

44

5

ANALYSIS OF SIMULATION RESULT…………………...

45-55

5.5

Simulation Results and Discussions………………………….

45

5.5.1

Simulation Result on the Basis of BER vs. SNR Ratio………

46

5.5.2

Simulation Result on the Basis of P(e) vs. SNR Ratio……….

51

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

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CONTENTS
CHAPTER

6

CONCLUSION & FUTURE WORK………………………..

56-57

6.1

Conclusion……………………………………………………...

56

6.2

Future Work…………………………………………………….

57

Lists of REFERENCES…………………………………………………………………

58

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

V

List of Figures
Figure 1.1 Illustration of the orthogonality between the subcarriers in OFDM………...

2

Figure 2.1 Conventional multicarrier technique FDM and OFDM……………………..

6

Figure 2.2 System model of OFDM using IFFT and FFT………………………………

10

Figure 2.3 Guard Interval (GI) and Cyclic prefix……………………………………….

11

Figure 3.1 Simple illustration of multipath channel with NLOS signal………………...

17

Figure 3.2 Simple illustration of multipath channel with LOS signal………………….

20

Figure 3.3 The AWGN Channel………………………………………………………...

21

Figure 3.4 Generation of BPSK…………………………………………………………

24

Figure 3.5 A BPSK signal………………………………………………………………

25

Figure 3.6 Constellation Diagram of BPSK…………………………………………….

25

Figure 3.7 QPSK Transmitter…………………………………………………………..

26

Figure 3.8 QPSK Receiver……………………………………………………………...

26

Figure 3.9 Constellation Diagram of QPSK…………………………………………….

27

Figure 3.10 Timing diagram for QPSK…………………………………………………..

28

Figure 3.11 Constellation Diagram of 16-QAM & 64-QAM………………………….....

30

Figure 4.1 Flow chart of the working principle………………………………………....

34

Figure 4.2 System model of OFDM communication system…………………………...

35

Figure 4.3 Probability error observation curve………………………………………….

41

Figure 4.4 Hierarchical representation of the m-files…………………………………...

43

Figure 5.1 BER performance of Rayleigh channel using BPSK, QPSK,
1

16-QAM and 64-QAM………………………………………………………

46

Figure 5.2 Bit error rate (BER) performance of Rician channel using BPSK, QPSK,
1

16-QAM and 64-QAM………………………………………………………

47

Figure 5.3 Bit error rate (BER) performance of AWGN channel using BPSK, QPSK,1
1

16-QAM and 64-QAM………………………………………………………

48

Figure 5.4 Probability of Error P(e) performance of Rayleigh channel using BPSK,
16-QAM and 64-QAM………………………………………………………

51

Figure 5.5 Probability of Error P(e) performance of Rician channel using BPSK,
16-QAM and 64-QAM………………………………………………………

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

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VI

List of Figures
Figure 5.6 Probability of Error P(e) performance of AWGN channel using BPSK,
16-QAM and 64-QAM………………………………………………………

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

53

VII

List of Tables
Table 1 Simulation Parameter………………………………………………………...

44

Table 2 Comparison Table for Rayleigh Channel Using Different Modulation
Technique on the Basis of BER Performance………………………………..

49

Table 3 Comparison Table for Rician Channel Using Different Modulation
Technique on the Basis of BER Performance………………………………..

50

Table 4 Comparison Table for AWGN Channel Using Different Modulation
Technique on the Basis of BER Performance………………………………..

50

Table 5 Comparison Table for Rayleigh Channel Using Different Modulation
Technique on the Basis of Probability Error Performance…………………..

54

Table 6 Comparison Table for Rician Channel Using Different Modulation
Technique on the Basis of Probability Error Performance…………………..

54

Table 7 Comparison Table for AWGN Channel Using Different Modulation
Technique on the Basis of Probability Error Performance…………………..

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

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VIII

Acronyms
ADC

Analog to Digital Conversion

ADSL

Asymmetric Digital Subscriber Line

AMC

Adaptive Modulation and Coding

ATM

Asynchronous Transfer Mode

AWGN

Additive White Gaussian Noise

BER

Bit Error Rate

BPSK

Binary Phase Shift Keying

BS

Base Station

CDMA

Code Division Multiple Access

CINR

Carrier to Interference-plus-Noise Ratio

CNR

Carrier to Noise Ratio

CP

Cyclic Prefix

CSI

Channel State Information

DAC

Digital to Analog Conversion

DFT

Discrete Fourier Transform

DSL

Digital Subscriber Line

DTDR

Direct Time-Domain Ranging

DVB

Digital Video Broadcasting

ETSI

European Telecommunications Standards Institute

FDD

Frequency Division Duplexing

FDM

Frequency Division Multiplexing

FDMA

Frequency Division Multiple Access

FDR

Frequency-Domain Ranging

FFT

Fast Fourier Transform

GMSK

Gaussian Minimum Shift Keying

IA

Interference Avoidance

IC

Interference Cancellation

ICI

Inter-Carrier Interference

IDFT

Inverse Discrete Fourier Transform

IEEE

Institute of Electrical and Electronics Engineers

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

IX

IFFT

Inverse Fast Fourier Transform

ISI

Inter-Symbol Interference

ITDR

Indirect Time-Domain Ranging

ITU

International Telecommunication Union

LAN

Local Area Network

LOS

Line of Sight

MC-CDMA Multicarrier Code Division Multiple Access
MS

Mobile Station

MUI

Multi-User Interference

NLOS

Non Line of Sight

OFDM

Orthogonal Frequency Division Multiplexing

OFDMA

Orthogonal Frequency Division Multiple Access

PAPR

Peak to Average Power Ratio

P (e)

Probability Error

PDP

Power Delay Profile

PHY

Physical Layer

PIC

Parallel Interference Cancellation

P/S

Parallel to Serial

PSK

Phase Shift Keying

QAM

Quadrature Amplitude Modulation

QPSK

Quadrature Phase Shift Keying

RF

Radio Frequency

rms

root mean square

RSS

Received Signal Strength

SIC

Successive Interference Cancellation

SNR

Signal to Noise Ratio

S/P

Serial to Parallel

STD

Standard Deviation

UMTS

Universal Mobile Telecommunications System

WLAN

Wireless Local Area Network

WiMAX

Worldwide Interoperability for Microwave Access

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

X

Chapter 1
Introduction

1.1

Purpose and Objectives

In wireless communications, the signal transmitted from the source typically experiences attenuation, scattering, and reflection and refraction before it reaches the destination. These effects are usually modeled as one or several values known as the channel response which is convolved with the transmitted signal. The response of the channel between the transmitter and the receiver is not fixed but varies with time and frequency. The bandwidth upon which the channel response can be assumed fixed (flat) is known as the coherence bandwidth of the channel. If the data is transmitted at high symbol rates, the bandwidth of the signal becomes wide and may exceed the coherence bandwidth of the channel. This distorts the signal and leads to inter symbol interference (ISI) [1]. ISI degrades the signal in two ways. First, previously transmitted symbols interfere with the current Symbol. Second, part of the current symbol energy is lost as it will cause ISI for sub sequent symbols. To eliminate ISI, equalization is usually employed. The equalizer is an adaptive digital filter with a certain number of taps. The weights of the taps in the equalizer are designed such that the combined response of the channel and equalizer is a constant value (flat) within the signal bandwidth. Equalizers suffer from a number of limitations. Finding the optimum weight of each tap is a complicated process which increases exponentially as the length (number of taps) of the filter increases. Moreover, these weights are calculated from a noisy estimate of the channel response and hence the estimation error will be higher compared to the single tap filter needed for flat channels [2]. Another limitation is equalizers are designed with a maximum length (number of taps). Such equalizers will perform poorly if the channel response is longer than the equalizer’s length. To eliminate the need for multi-tap equalizers, it was proposed in the 1960s that the data be split into parallel streams, thus reducing the symbol rate and bandwidth of each stream. If the number of streams is large enough, the bandwidth of each stream can become less than the channel coherence bandwidth and hence each stream experiences a flat channel response. These streams are then modulated using separate orthogonal carriers known as subcarriers. The subcarriers must fit within the
PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

1

bandwidth allocated for transmission but must be far enough so that they do not interfere with each other. The minimum spacing between the subcarriers was found to be 1/T where T is the symbol duration after splitting the data into parallel streams [3, 8].

Fig.1.1 shows the spectrum of data modulated using subcarriers with 1/T spacing. The transmission scheme proposed in the 1960s suffered from two limitations. First, a separate modulator is required for each stream hence increasing the cost of the system. Second, any frequency synchronization errors will lead to interference between the subcarriers (see Fig.1).
The risk of interference due to frequency errors can be reduced by increasing the separation between the subcarriers at the expense of bandwidth efficiency [3, 8 and 9].

Figure 1.1: Illustration of the orthogonality between the subcarriers in OFDM [1]

1.2

Background

The idea, which was proposed in mid-1960s, used parallel data transmission and frequency division multiplexing (FDM) [1, 14]. In the 1960s, the OFDM technique was used in several high frequency military systems
•

KINEPLEX [15]

•

ANDEFT [16]

•

KATHRYN [17]

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

2

In 1971, Weinstein and Ebert applied the Discrete Fourier Transform (DFT) to parallel data transmission systems as part of modulation and demodulation process [1, 4 and 18]. It’s known as FFT-based OFDM.
In the 1980s, OFDM was studied for high-speed modems digital mobile communication, and high-density recording. A Pilot tone is used to stabilize carrier and frequency control. A Trellis code is implemented.
In 1980, Hirosaki suggested an equalization algorithm in order to suppress both Inter symbol and
Inter carrier interference caused by the channel impulse response or timing and frequency errors
[4, 19]. Hirosaki also introduced the DFT-based implementation of Saltsburg’s O-QAM OFDM system [4, 20]
In the 1990s, OFDM was exploited for wideband data communications [1-7]
1) Mobile radio FM channels
2) Fix-wire network [7, 26]
•

High-bit-rate digital subscriber line (HDSL)

•

Asymmetric digital subscriber line (ADSL)

•

Very-high-speed digital subscriber line (VDSL)

3) Digital audio broadcasting (DAB) [9, 21],
4) Digital video broadcasting (DVB)
5) High-definition television (HDTV) terrestrial broadcasting [10, 22]
•

There exist three mechanisms about the digital terrestrial television broadcasting system in European (COFDM), North America (8-VSB) and
Japan (BST-OFDM).

6) Wireless LAN [11-13, 23-25]
•

HIPERLAN2 (European)

•

IEEE 802.11a (U.S.A)

•

IEEE 802.11g (U.S.A)

Now, OFDM technique has been adopted as the new European DAB standard and HDTV standard. It is also a candidate of 4G mobile communication.
•

OFDM/UWB (802.15.3a)

•

IEEE 802.16 broadband wireless access system

•

IEEE 802.20 mobile broadband wireless access (MBWA)

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

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1.3

Aims and Objectives
Our main aim is to enhance the ability of OFDM communication system by using suitable channel and modulation technique.
While doing the work, our goal was :
•

To calculate the performance on the basis of BER vs. SNR ratio of an
OFDM system for AWGN channel, Rayleigh channel and Rician channel.

•

To calculate the P(e) vs. SNR ratio of an OFDM system for AWGN channel, Rayleigh fading & Rician fading.

•

To compare different modulation techniques and different channels for
OFDM system.

•
•

1.4

To determine the suitable channel for OFDM system.
To determine the suitable modulation technique for OFDM system.

Paper Layout

This paper is organized by different points.
In chapter 2 we will discuss about the overall scenario of OFDM communication system. Basic principle of OFDM will help to get basic knowledge on OFDM communication system. The theory and applications of OFDM with the advantages and disadvantages will be discussed.
For fulfilling the demand of today’s communication system, OFDM communication system may face some challenges. This also will be discussed later.
In chapter 3 we will discuss about the channel environment and modulation scenario. Channel environment section will discuss several channels that we used for our research purpose of
OFDM communication system.
The section of modulation scenario will describe the different modulation techniques that we used for our research purpose of OFDM communication system.
In chapter 4 we will explain the working procedure of our research. How we accomplished the whole work and what limitations we faced during the work will be discussed on that section.
Chapter 5 is all about the simulation result and the discussion of the result. What output carried by our research will be discussed on that section.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

4

Chapter 6 will provide a conclusion of our research on the basis of our simulation output. Later we added a section about the work that we didn’t accomplish.
At last, we added a list of papers about the previous work of the related sector as a reference.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

5

Chapter 2
Orthogonal Frequency Division Multiplexing (OFDM)

2.1

Basic Principle of OFDM

Orthogonal Frequency Division Multiplexing (OFDM) is becoming a very common multi-carrier modulation technique for transmission of signals over wireless channels in diverse environments.
OFDM divides the high rate stream into parallel lower rate data and hence prolongs the symbol duration, thus helping to eliminate Inter Symbol Interference (ISI). In an OFDM system the sub channels overlap with each other to a certain extent as can be seen in figure 2.1 in which leads to the reduced use of bandwidth and since these carriers are orthogonal to each other Inter Carrier
Interference (ICI) is also reduced. The input data sequence is mapped into symbols, which are distributed and sent over the N parallel sub-channels, one symbol per channel. To permit dense packing and still guarantee that a minimum of interference between the sub channels is encountered, the carrier frequencies must be chosen carefully. Using orthogonal carriers, which in the frequency domain can be viewed so as the frequency distance between two sub-carriers is given by the distance to the first spectral null.

Figure 2.1: (a) Conventional multicarrier technique (FDM) [1]
(b) OFDM technique [1]
PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

6

2.2

Theory of OFDM

The transmitted signal s(t) using several independent carriers is given by [8, 10, 11]:
N −1

s (t ) =

∑ d ( p , t )e

j ( 2 π f c + p ∆ω) t

p =0
N −1

=e

j 2π f c t

× ∑ d ( p, t )e j . p .∆ω t

(2.1)

p =0

Where d(p,t) is the data for stream p which also represent the subcarrier index, ∆ω is the frequency spacing, fc is the frequency of the first subcarrier, t is the time, N is the number of subcarriers and j is the square root of -1. The receiver samples the received signal, hence, we rewrite Eq.(1) for discrete time (t= nT) to get
N −1

s(n) = e

j .2π fc .nT

× ∑ d ( p, n) e j. p∆wnT

(2.2)

p =0

For subcarriers with frequency spacing of 1/NT, Eq. (2) becomes:

s(n) = Ne

j.2π fc .nT

2π j . p.n
1 N−1
× ∑d( p, n) e N
N p=0

(2.3)

Considering the summation on the right hand of Eq. (3) we note that this is the Inverse Discrete
Fourier Transform (IDFT) with d (p, n) the data at subcarrier p at a time sample n. The IDFT can be calculated efficiently using any of the existing Inverse Fast Fourier Transform (IFFT) algorithms. The first factor on the right hand side of Eq. (3) is a multiplication by a carrier that can be achieved by a modulator. Hence, instead of using N modulators, we can combine an IFFT with a single modulator to achieve the same performance. The receiver first demodulates the signal to remove the first multiplicative factor on the right hand side of Eq. (3), then uses a Fast
Fourier Transform algorithm to recover the data d (p, n) from the summation of Eq. (3). Ignoring the CP for now, the transmitted OFDM signal s(n) consists of the N output values from the IFFT
(known as the OFDM symbol) and is transmitted serially with a symbol rate equal to N/T. Hence, the transmitted OFDM signal experiences a frequency selective fading channel as it has N times the bandwidth of individual streams. We prove next that the processing done at the transmitter and receiver, converts this channel into a set of flat fading channels.
PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

7

First, we approximate the channel response with a finite impulse filter (FIR) of length M where
(M < N), and we consider a single transmitted OFDM symbol. The received signal r(n) after demodulating the carrier frequency (fc) is given by:
M −1

r (n) = ∑ s(n − l ) zl (n) + w(n)

(2.4)

l =0

Where Zl (n) is the channel response of tap l at time index n and w(n) is the noise sample. The signal at subcarrier k[x(k)] after the FFT processes the received signal r(n) after demodulating the carrier frequency (fc) is given by:
N −1

∑ r (n )e

x(k ) =

−j

2π k .n
N

n=0
N −1 M −1

= ∑∑ s(n − l )zl (n) e

−j

2π k .n
N

n=0 l =0

N −1

+ ∑w(n) e

−j

2π k .n
N

n=0

2π
2π
2π
− j k.n N −1
− j p( n−l )  N −1
− j k.n
1 N−1 M −1
N
N
= ∑∑ Zl (n)e
 + ∑w(n).e N
∑d( p, n) e
N n=0 p=0  p=0  n=0
2π
2π
2π
p .n − j k . n M −1 p .t 
−j
−j

N
N
e
∑0 ∑0  d ( p , n )e
∑ zl ( n ) e N  n= p =  l =0

N −1 N −1

1
=
N
N −1

+ ∑ w ( n ).e

−j

2π k .n
N

(2.5)

n =0

Let the N point FFT of the channel response zl(n) is:
N −1

∑ z (n).e

−j

2π k .l
N

l

= h (n, k )

(2.6)

l =0

N−1

−j

h (n, p) = ∑zl (n).e l =0

2π
p.l
N

M −1

−j

= ∑zl (n).e

2π
p.l
N

(2.7)

l =0

Since it is assumed that the channel response has a maximum length M which is shorter than N, z(n) is equal to 0 for l ≥ M.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

8

Substituting (7) in (5), we get:
2π
2π j n. p − j n.k
1 N −1 N −1
N
x(k) = ∑∑d ( p, n). h (n, p).e
.e N + w (k)
N l =0 p=0

(2.8)

w(k) is the N point FFT of the noise samples. If the channel does not vary within the OFDM symbol we have:

h (n, p ) = h ( p )

(2.9)

The data d(p,n) remains fixed for the duration of the OFDM symbol, hence:

d ( p, n) = h( p, o) = d ( p)

(2.10)

Substituting (9) and (10) in (8) we get:
2π
N −1 j n ( p −k )
1 N −1 x(k ) = ∑ d ( p). h( p).∑ e N
+ w(k )
N l =0 n =0
N −1

= ∑ d ( p). h( p). δ( p − k ) + w(k )

(2.11)

p =0

δ(p-k) is the shifted Dirac-Delta function. Therefore Eq. (11) reduces to:

x (k) = d(k). h (k) + w(k)

(2.12)

Ignoring the noise, dividing x(k) by the channel response h(k) yields the transmitted data. From the above analysis, we note that the IFFT and FFT algorithms used at the transmitter and receiver eliminated the ISI between the symbols within the OFDM symbol (Intra OFDM ISI). However, if consecutive OFDM symbols are transmitted, ISI between different OFDM symbols occurs
(Inter-OFDM ISI) and this cannot be resolved.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

9

2.3

OFDM System Model

The concept of using parallel-data transmission, Frequency Division Multiplexing (FDM) was first published in the midterm of 1960s. The basic idea was to use parallel data and FDM with overlapping sub-channels to avoid the use of high-speed equalization to combat impulsive noise, multipath distortion and fully utilize bandwidth. Although the idea of OFDM was conceived in 1960s, it was not realizable until the advent of FFT. With the advent of FFT/IFFT it became possible to generate OFDM using the digital domain for orthogonality of subcarriers.
Figure 2.2, shows a block diagram of a discrete time OFDM system, where an N complex valued data symbol modulates N orthogonal carriers using the IFFT forming. The transmitted
OFDM signal multiplexes N low-rate data streams, each experiencing an almost flat fading channel when transmitted.

Figure 2.2: System model of OFDM using IFFT and FFT [2]

In OFDM, Guard Interval (GI) is introduced because of multipath propagation as it affects the symbols to delay and attenuate, which causes Inter Symbol Interference (ISI). In GI, Cyclic
Prefix (CP) is used to counter Inter Carrier interference (ICI) within an OFDM frame.

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Figure 2.3: Guard Interval (GI) and Cyclic prefix [2]
In single carrier systems each symbol occupying an entire bandwidth could be lost due to frequency selective fading, but when transmitted on low data parallel streams, symbol time increases and channel become flat fading [1].OFDM structure basically relies on three principles:
•

The IFFT and FFT [8] are used for modulating and demodulating individual OFDM sub-carriers to transform the signal spectrum to the time domain for transmission over the channel and then by employing FFT on the receiving end to recover data symbols in serial order.

•

The second key principle is the cyclic prefix (CP) as Guard Interval (GI). CP keeps the transmitted signal periodic. One of the reasons to apply CP is to avoid Inter
Carrier Interference (ICI).

• Interleaving is the third most important concept applied. The radio channel may affect the data symbols transmitted on one or several sub carriers which lead to bit errors. To encounter this issue we use efficient coding schemes [1].
The CP is simply a copy of the last symbols of the samples placed first, making the signal appear as periodic in the receiver as shown in Figure 2.3. Before demodulating the OFDM signal the CP is removed. By exploiting the structure imposed using CP. Symbol synchronization can be achieved. Due to the carrier orthogonality it is possible to use the
Discrete Fourier Transform (DFT) and the Inverse Discrete Fourier Transform (IDFT) for modulation and demodulation of the signal. To obtain high spectral efficiency, there can be different modulation schemes can be applied. We will be using BPSK, QPSK, 16-QAM and
64-QAM.

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This paper mainly deals with the performance of the OFDM system under Rayleigh, Rician and
AWGN fading environments. Though the total channel is a frequency selective channel, the channel experienced by each subcarrier in an OFDM system is a flat fading channel.

2.4

Advantages and Disadvantages of OFDM

As a multicarrier system, OFDM has several advantages at the communication sector. But it has some disadvantages also. In some specific sectors it shows its limitations too.
The advantages of OFDM
•

Immunity to delay spread and multipath

•

Resistance to frequency selective fading

•

Simple equalization

•

Efficient bandwidth usage

The disadvantages of OFDM
•

Synchronization needed

•

Need FFT units at transmitter, receiver

•

Sensitive to carrier frequency offset

•

High peak to average power ratio

Limitations of OFDM
•

Timing synchronization error- If MC OFDM DS-CDMA system does not synchronize whole process then proper signal will not be received at receiver side.

•

Doppler frequency shift- Due to Doppler Effect, there will be offset in carrier frequency. •

Frequency selective fading.

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2.5

Application of OFDM

Due to the remarkable advantages of OFDM, it has many applications. Now-a-days the multicarrier transmission techniques contribute a lot in the field of communications. Some of the important applications are:
•

Digital Audio Broadcasting (DAB)

• Higher Definition Television (HDTV)
In bellow here briefly discuss about the application and working principle of DAB and HDTB.

2.5.1

Digital Audio Broadcasting (DAB)

Current analog FM radio broadcasting system cannot satisfy the demands of the future, which are: •

Excellent sound quality

•

Large number of stations

•

Small portable receivers

No quality impairment due to multipath propagation or signal fading. Here current analog FM radio broadcasting systems have reached the limits of technical improvement.
DAB is a digital technology offering considerable advantages over today's FM radio, both to listeners and broadcasting. DAB's flexibility will also provide a wider choice of programs, including many not available on FM. A single station might offer its listeners a choice of mono voice commentaries on three or four sporting events at the same time, and then combine the bit streams to provide high-quality sound for the concert which follows. DAB combines two advanced digital technologies to achieve robust and spectrum-efficient transmission of highquality audio and other data. DAB uses the MPEG Audio Layer II system to achieve a compression ratio of 7:1 without perceptible loss of quality. The signal is then encoded at a bit rate of 8-384 Kbit/s, depending on the desired sound quality and the available bandwidth. Signal is individually error protected and labeled prior to multiplexing. Independent data services are similarly encoded.

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2.5.2

Higher Definition Television (HDTV)

Commercial television station is first published by England. There exist three mechanisms about the digital terrestrial television broadcasting system in European (COFDM), North America (8VSB), and Japan (BST-OFDM).
The European introduces the COFDM modulation scheme into the system structure.
American develops the system based on 8-level vestigial side-band (8-VSB) modulation scheme. Japan is zealous to develop the band segmented transmission Orthogonal Frequency
Division Multiplexing (BST-OFDM) system, which nature is based on COFDM modulation scheme.

A. System Overview
Operate within existing VHF and UHF spectrum.
OFDM with concatenated error correcting coding is being specified.
Flexible guard interval is specified.
Two mode of operations :
•

2K mode: suitable for single transmitter operation for small SFN networks.

•

8K mode: used both for single transmitter operation and for small and large
SFN networks.

Multi-level QAM modulation.
Different inner code rates (punctured convolution code).
MPEG stream is separated into
•

High-priority stream

•

Low-priority stream

Unequal error protection (UEP)

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2.6

Challenges facing OFDM

Beside the usual synchronization, channel estimation and noise issues encountered in most transmission systems, OFDM systems face two unique problems. The first is its high peak to average power ratio and the other is the inter-carrier interference caused by mobility.

2.6.1

Peak to Average Power Ratio

In OFDM, the transmitted signal is obtained by taking the IFFT of the input data. The main issue with this technique is that some input combinations can lead to OFDM symbols with high amplitudes. To illustrate this, consider a long sequence of 1s to be transmitted. If the input to the
IFFT is a sequence of ones, the output will be a delta function (i.e. the first value in the OFDM symbol is very high, followed by a sequence of zeros). The average power of the whole OFDM symbol is the same as other input combinations, but the peak power is a high value leading to high peak to average power ratio. In practical systems amplifiers are used in their linear region to amplify the signal. High peak to average power ratio means the amplifier must have a large linear region in order to avoid distortion when the amplifier reaches saturation. Amplifiers with such characteristics are usually very expensive, especially at high frequencies. To overcome this problem, coding can be used prior to the IFFT. The coding used aims at avoiding input combinations (e.g. long sequence of 1s) that will lead to OFDM symbols with high peak power.

2.6.2

Mobility

OFDM performs well in fixed and slowly varying channels. However, in fast fading channels, an irreducible error floor is encountered at high signal to noise ratios (SNR) due to intercarrier interference (ICI). In mobile links, if a transmitter sends a sinusoidal signal, its bandwidth becomes broader at the receiver due to the Doppler shift [3, 5 and 6]. This shift in frequency is a minor issue in single carrier systems, but in OFDM systems the orthogonality of the subcarriers
(see Fig.1.1) is destroyed by Doppler shift leading to interference between the carriers (ICI).

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Chapter 3
Literature Survey

3.1

Channel Environment

In telecommunications and computer networking, a communication channel, or channel, refers either to a physical transmission medium such as a wire, or to a logical connection over a multiplexed medium such as a radio channel. A channel is used to convey an information signal, for example a digital bit stream, from one or several senders (or transmitters) to one or several receivers. A channel has a certain capacity for transmitting information, often measured by its bandwidth in Hz or its data rate in bits per second.
Communicating data from one location to another requires some form of pathway or medium.
These pathways, called communication channels, use two types of media: cable (twisted-pair wire, cable, and fiber-optic cable) and broadcast (microwave, satellite, radio, and infrared). Cable or wire line media use physical wires of cables to transmit data and information. Twisted-pair wire and coaxial cables are made of copper, and fiber-optic cable is made of glass.
For our research we used
•

Rayleigh fading channel

•

Rician fading channel

• AWGN channel
3.1.1

Rayleigh fading

Rayleigh fading is the name given to the form of fading that is often experienced in an environment where there are a large number of reflections present. The Rayleigh fading model uses a statistical approach to analyze the propagation, and can be used in a number of environments. The Rayleigh fading model is normally viewed as a suitable approach to take when analyzing and prediction radio wave propagation performance for areas such as cellular communications in a well built up urban environment where there are many reflections from buildings, etc. HF ionospheric radio wave propagation where reflections (or more exactly refractions) occur at
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16

many points within the ionosphere is also another area where Rayleigh fading model applies well. It is also appropriate to use the Rayleigh fading model for tropospheric radio propagation because, again there are many reflection points and the signal may follow a variety of different paths. Transmitter

Receiver

Figure 3.1: Simple illustration of multipath channel with NLOS signal [5].
The Rayleigh propagation model is most applicable to instances where there are many different signal paths, none of which is dominant. In this way all the signal paths will vary and can have an impact on the overall signal at the receiver.
The Rayleigh fading model is particularly useful in scenarios where the signal may be considered to be scattered between the transmitter and receiver. In this form of scenario there is no single signal path that dominates and a statistical approach is required to the analysis of the overall nature of the radio communications channel.
Rayleigh fading is a model that can be used to describe the form of fading that occurs when multipath propagation exists. In any terrestrial environment a radio signal will travel via a number of different paths from the transmitter to the receiver. The most obvious path is the direct, or line of sight path.
However there will be very many objects around the direct path. These objects may serve to reflect, refract, etc the signal. As a result of this, there are many other paths by which the signal may reach the receiver.

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When the signals reach the receiver, the overall signal is a combination of all the signals that have reached the receiver via the multitude of different paths that are available. These signals will all sum together, the phase of the signal being important. Dependent upon the way in which these signals sum together, the signal will vary in strength. If they were all in phase with each other they would all add together? However this is not normally the case, as some will be in phase and others out of phase, depending upon the various path lengths, and therefore some will tend to add to the overall signal, whereas others will subtract.
As there is often movement of the transmitter or the receiver this can cause the path lengths to change and accordingly the signal level will vary. Additionally if any of the objects being used for reflection or refraction of any part of the signal moves, then this too will cause variation. This occurs because some of the path lengths will change and in turn this will mean their relative phases will change, giving rise to a change in the summation of all the received signals.
The Rayleigh fading model can be used to analyze radio signal propagation on a statistical basis.
It operates best under conditions when there is no dominant signal (e.g. direct line of sight signal), and in many instances cellular telephones being used in a dense urban environment fall into this category. Other examples where no dominant path generally exists are for ionospheric propagation where the signal reaches the receiver via a huge number of individual paths.
Propagation using tropospheric ducting also exhibits the same patterns. Accordingly all these examples are ideal for the use of the Rayleigh fading or propagation model.
Rayleigh fading is a rational model when there are many objects in the environment that scatter the transmitted signal before it arrives at the receiver. The central limit theorem holds that, if there is sufficiently much scatter, the channel impulse response will be well-modeled as a
Gaussian process regardless of the distribution of the individual components [3].
When there are large numbers of paths, applying Central Limit Theorem, each path can be modeled as circularly symmetric complex Gaussian random variable with time as the variable.
This model is called Rayleigh fading channel model [4]. If there is no dominant component to the scatter, then such a process will have zero mean and phase evenly distributed between 0 and
2π radians. The envelope of the channel response will therefore be Rayleigh distributed.
A circularly symmetric complex Gaussian random variable is of the form

Z = X + jY

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(3.1)

18

where real and imaginary parts are zero mean Independent and Identically Distributed (IID)
Gaussian random variables.
For a circularly symmetric complex random variable,

E(z) = E [e jθ z] = e jθ (z)

(3.2)

The statistics of a circularly symmetric complex Gaussian random variable is completely specified by the variance,

σ2 = E [z2]

(3.3)

The magnitude |Z|, which has a Probability Density Function (PDF), p(z) is called the Rayleigh random Variable.
− z2

p( z ) =

3.1.2

z 2 σ2 e ,
2
σ

z>0

(3.4)

Rician Fading

Rician fading is a stochastic model for radio propagation anomaly caused by partial cancellation of a radio signal by itself -the signal arrives at the receiver by several different paths (hence exhibiting multipath interference), and at least one of the paths is changing (lengthening or shortening). Rician fading occurs when one of the paths, typically a line of sight signal, is much stronger than the others. In Rician fading, the amplitude gain is characterized by a Rician distribution. The model behind Rician fading is similar to that for Rayleigh fading, except that in Rician fading a strong dominant component is present. This dominant component can for instance be the line-of-sight wave. Refined Rician models also consider that, the dominant wave can be a phasor sum of two or more dominant signals, e.g. the line-of-sight, plus a ground reflection.
This combined signal is then mostly treated as a deterministic (fully predictable) process, and that the dominant wave can also be subject to shadow attenuation. This is a popular assumption in the modeling of satellite channels.
Besides the dominant component, the mobile antenna receives a large number of reflected and scattered waves.

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Rician Fading is a non-deterministic model for the anomaly that occurs when a transmitted signal accidentally cancels itself. The signal arrives at the receiver by several different, and at least one of the paths is changing. Rician fading occurs when one of the paths, typically a line of sight signal, is much stronger than the others. In Rician fading, the amplitude gain is characterized by a Rician distribution. When there isn’t any line of sight path occurring between the OFDM transmitter and the receiver than the Rican Fading can be categorized by
Rayleigh Fading [5].
Rician Fading [10] channel can be defined using two parameters: k and Ω , where k is called the Rice Factor and it is the ratio between the power in the direct path and the power in the other, scattered, paths and Ω is the total power from both paths and acts as a scaling factor to the distribution.

Multipath

Direct path
(LOS)
Receiver

Transmitter

Figure 3.2: Simple illustration of multipath channel with LOS signal [4].
The received signal amplitude not considering the power R is then Rice distributed with parameters: v2 =

k
Ω
1+ k2

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(3.5)

20

And,

σ

2

=

Ω
2 (1 + k )

(3.6)

The resulting Probability Density Function (PDF) is then given by-


2(k +1)x
(k +1)x2   k(k +1)  f (x) = exp  −k − x . l0  2

Ω
Ω  
Ω



3.1.3

(3.7)

AWGN Channel

Additive white Gaussian noise (AWGN) is a channel model in which the only impairment to communication is a linear addition of wideband or white noise with a constant spectral density
(expressed as watts per hertz of bandwidth) and a Gaussian distribution of amplitude. The model does not account for fading, frequency selectivity, interference, nonlinearity or dispersion.
However, it produces simple and tractable mathematical models which are useful for gaining insight into the underlying behavior of a system before these other phenomena are considered.
Additive White Gaussian Noise (AWGN) [10] channel adds White Gaussian noise to the signal when it is passed through the channel. In the case of white Gaussian noise the values at any pair of times are identically distributed and statistically independent on each other.

Figure 3.3: The AWGN Channel [4].

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21

The above figure shows the diagram of a AWGN channel, where n(t) is the noise waveform, u(t) is the modulated signal and A is the overall pathloss.
So the received signal y(t) is given by

y(t) = Au(t) + n(t)

(3.7)

AWGN channel is not associated with either fading or any other system parameters. It is just the noise that is added to the OFDM modulated signal when it is travelling through the channel. Wideband Gaussian noise comes from many natural sources, such as the thermal vibrations of atoms in conductors (referred to as thermal noise or Johnson-Nyquist noise), shot noise, black body radiation from the earth and other warm objects, and from celestial sources such as the Sun.
The AWGN channel is a good model for many satellite and deep space communication links. It is not a good model for most terrestrial links because of multipath, terrain blocking, interference, etc. However, for terrestrial path modeling, AWGN is commonly used to simulate background noise of the channel under study, in addition to multipath, terrain blocking, interference, ground clutter and self interference that modern radio systems encounter in terrestrial operation.

C =

1 p  lo g  1 + 
2
n 


(3.8)

Where C is the channel capacity.

3.2

Modulation Scenario

In electronics and telecommunications, modulation is the process of varying one or more properties of periodic waveform, called the carrier signal, with a modulating signal which typically contains information to be transmitted.
In telecommunications, modulation is the process of conveying a message signal, for example a digital bit stream or an analog audio signal, inside another signal that can be physically transmitted. Modulation of a sine waveform is used to transform a baseband message signal into a pass band signal.
A device that performs modulation is known as a modulator and a device that performs the inverse operation of modulation is known as demodulator (sometimes detector or demod). A device that can do both operations is a modem (from "modulator–demodulator").

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The aim of digital modulation is to transfer a digital bit stream over an analog bandpass channel, for example over the public switched telephone network (where a bandpass filter limits the frequency range to between 300 and 3400 Hz), or over a limited radio frequency band.
The aim of analog modulation is to transfer an analog baseband (low pass) signal, for example an audio signal or TV signal, over an analog bandpass channel at a different frequency, for example over a limited radio frequency band or a cable TV network channel.
Analog and digital modulation facilitate frequency division multiplexing (FDM), where several low pass information signals are transferred simultaneously over the same shared physical medium, using separate passband channels (several different carrier frequencies).
The aim of digital baseband modulation methods, also known as line coding, is to transfer a digital bit stream over a baseband channel, typically a non-filtered copper wire such as a serial bus or a wired local area network.
The aim of pulse modulation methods is to transfer a narrowband analog signal, for example a phone call over wideband baseband channel or in some of the schemes, as a bit stream over another digital transmission system.

3.2.1

Binary phase-shift keying (BPSK)

BPSK (also sometimes called PRK, phase reversal keying or 2PSK) is the simplest form of phase shift keying (PSK). It uses two phases which are separated by 180° and so can also be termed 2PSK. It does not particularly matter exactly where the constellation points are positioned, and in this figure they are shown on the real axis, at 0° and 180°. This modulation is the most robust of all the PSKs since it takes the highest level of noise or distortion to make the demodulator reach an incorrect decision. It is, however, only able to modulate at 1 bit/symbol (as seen in the figure) and so is unsuitable for high data-rate applications.
In the presence of an arbitrary phase-shift introduced by the communications channel, the demodulator is unable to tell which constellation point is which. As a result, the data is often differentially encoded prior to modulation.
BPSK is functionally equivalent to 2-QAM modulation. Consider a sinusoidal carrier. If it is modulated by a bi-polar bit stream according to the scheme illustrated in Figure 1, its polarity will be reversed every time the bit stream changes polarity.

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23

This, for a sine wave, is equivalent to a phase reversal (shift). The multiplier output is a BPSK signal. Figure 3.4: Generation of BPSK [8]

The information about the bit stream is contained in the changes of phase of the transmitted signal. A synchronous demodulator would be sensitive to these phase reversals.

Figure 3.5: A BPSK signal [8].
A snap-shot of a BPSK signal in the time domain is shown in Figure 3.3 (lower trace). The upper trace is the binary message sequence.
In below their shown the constellation diagram of BPSK system and should be illustrated the binary value.

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Figure 3.6: Constellation Diagram of BPSK [8].

3.2.2

Quadrature phase-shift keying (QPSK)

Sometimes this is known as quaternary PSK, quadriphase PSK, 4-PSK, or 4-QAM. (Although the root concepts of QPSK and 4-QAM are different, the resulting modulated radio waves are exactly the same.) QPSK uses four points on the constellation diagram, equispaced around a circle. With four phases, QPSK can encode two bits per symbol, shown in the diagram with gray coding to minimize the bit error rate (BER) sometimes misperceived as twice the BER of BPSK.
QPSK systems can be implemented in a number of ways. An illustration of the major components of the transmitter and receiver structure is shown below.

Figure 3.7: QPSK Transmitter [7].
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25

Figure 3.8: QPSK Receiver [7]

The mathematical analysis shows that QPSK can be used either to double the data rate compared with a BPSK system while maintaining the same bandwidth of the signal, or to maintain the data-rate of BPSK but halving the bandwidth needed. In this latter case, the BER of QPSK is exactly the same as the BER of BPSK and deciding differently is a common confusion when considering or describing QPSK.
Comparing the functions of BPSK, shows clearly how QPSK can be viewed as two independent
BPSK signals. Note that the signal-space points for BPSK do not need to split the symbol (bit) energy over the two carriers in the scheme shown in the BPSK constellation diagram.

Figure 3.9: Constellation Diagram of QPSK [7].

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26

Given that radio communication channels are allocated by agencies such as the Federal
Communication Commission giving a prescribed (maximum) bandwidth, the advantage of
QPSK over BPSK becomes evident: QPSK transmits twice the data rate in a given bandwidth compared to BPSK at the same BER. The engineering penalty that is paid is that QPSK transmitters and receivers are more complicated than the ones for BPSK. However, with modern electronics technology, the penalty in cost is very moderate.
The modulated signal is shown below for a short segment of a random binary data-stream. The two carrier waves are a cosine wave and a sine wave, as indicated by the signal-space analysis above. Here, the odd-numbered bits have been assigned to the in phase component & the evennumbered bits to the quadrature component (taking the first bit as number 1). The total signal of the sum of the two components is shown at the bottom. Jumps in phase can be seen as the PSK changes the phase on each component at the start of each bit-period. The topmost waveform alone matches the description given for BPSK above.

Figure 3.10: Timing diagram for QPSK [7].

3.2.3

Quadrature Amplitude Modulation (QAM)

Quadrature amplitude modulation (QAM) is both an analog and a digital modulation scheme. It conveys two analog message signals, or two digital bit streams, by changing (modulating) the amplitudes of two carrier waves, using the amplitude-shift keying (ASK) digital modulation scheme or amplitude modulation (AM) analog modulation scheme. The two carrier waves,
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27

usually sinusoids, are out of phase with each other by 90° and are thus called quadrature carriers or quadrature components hence the name of the scheme. The modulated waves are summed, and the resulting waveform is a combination of both phase-shift keying (PSK) and amplitude shift keying (ASK), or (in the analog case) of phase modulation (PM) and amplitude modulation.
In the digital QAM case, a finite number of at least two phases and at least two amplitudes are used. PSK modulators are often designed using the QAM principle, but are not considered as
QAM since the amplitude of the modulated carrier signal is constant. QAM is used extensively as a modulation scheme for digital telecommunication systems. Arbitrarily high spectral efficiencies can be achieved with QAM by setting a suitable constellation size, limited only by the noise level and linearity of the communications channel.

A. Analogue and Digital QAM
Quadrature amplitude modulation, QAM may exist in what may be termed either analogue or digital formats. The analogue versions of QAM are typically used to allow multiple analogue signals to be carried on a single carrier. For example it is used in PAL and NTSC television systems, where the different channels provided by QAM enable it to carry the components of chroma or colour information. In radio applications a system known as C-QUAM is used for AM stereo radio. Here the different channels enable the two channels required for stereo to be carried on the single carrier.
Digital formats of QAM are often referred to as “Quantized QAM” and they are being increasingly used for data communications often within radio communication systems. Radio communications systems ranging from cellular technology through wireless systems including
WiMAX, and Wi-Fi 802.11 use a variety of forms of QAM, and the use of QAM will only increase within the field of radio communications.

B. Quantized QAM
Like many digital modulation schemes, the constellation diagram is a useful representation. In
QAM, the constellation points are usually arranged in a square grid with equal vertical and horizontal spacing, although other configurations are possible (e.g. Cross-QAM). Since in digital telecommunications the data are usually binary, the number of points in the grid is usually a power of 2 (2, 4, 8…). Since QAM is usually square, some of these are rare the most common
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28

forms are 16-QAM, 64-QAM and 256-QAM. By moving to a higher-order constellation, it is possible to transmit more bits per symbol. However, if the mean energy of the constellation is to remain the same (by way of making a fair comparison), the points must be closer together and are thus more susceptible to noise and other corruption; this results in a higher bit error rate and so higher-order QAM can deliver more data less reliably than lower-order QAM, for constant mean constellation energy. Using higher-order QAM without increasing the bit error rate requires a higher signal-to-noise ratio (SNR) by increasing signal energy, reducing noise, or both. Figure 3.11: (a) Constellation Diagram of 16-QAM [7]
(b) Constellation Diagram of 64-QAM [7]
If data-rates beyond those offered by 8-PSK are required, it is more usual to move to QAM since it achieves a greater distance between adjacent points in the I-Q plane by distributing the points more evenly. The complicating factor is that the points are no longer all the same amplitude and so the demodulator must now correctly detect both phase and amplitude, rather than just phase.
64-QAM and 256-QAM are often used in digital cable television and cable modem applications.
In the United States, 64-QAM and 256-QAM are the mandated modulation schemes for digital cable (see QAM tuner) as standardized by the SCTE in the standard ANSI/SCTE 07 2000. Note that many marketing people will refer to these as QAM-64 and QAM-256. In the UK, 64-QAM is used for digital terrestrial television (Free view and Top up TV) and 256-QAM is used for free view-HD. PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

29

Communication systems designed to achieve very high levels of spectral efficiency usually employ very dense QAM constellations. For example current Home-plug AV2 500-Mbit power line Ethernet devices use 1024-QAM and 4096-QAM modulation, as well as future devices using
ITU-T G.hn standard for networking over existing home wiring (coaxial cable, phone lines and power lines); 4096-QAM provides 12 bits/symbol. Another example is VDSL2 technology for copper twisted pairs, whose constellation size goes up to 32768 points.

C. QAM Advantages and Disadvantages
Although QAM appears to increase the efficiency of transmission for radio communications systems by utilizing both amplitude and phase variations, it has a number of drawbacks. The first is that it is more susceptible to noise because the states are closer together so that a lower level of noise is needed to move the signal to a different decision point. Receivers for use with phase or frequency modulation are both able to use limiting amplifiers that are able to remove any amplitude noise and thereby improve the noise reliance. This is not the case with QAM.
The second limitation is also associated with the amplitude component of the signal. When a phase or frequency modulated signal is amplified in a radio transmitter, there is no need to use linear amplifiers, whereas when using QAM that’s contains an amplitude component, linearity must be maintained. Unfortunately linear amplifiers are less efficient and consume more power, and this makes them less attractive for applications.

3.3

QAM Noise Margin

While higher order modulation rates are able to offer much faster data rates and higher levels of spectral efficiency for the radio communications system, this comes at a price. The higher order modulation schemes are considerably less resilient to noise and interference.
As a result of this, many radio communication systems now use dynamic adaptive modulation techniques. They sense the channel conditions and adapt the modulation schemes to obtain the highest data rate for the some condition. As signal to noise ratios decrease error will increase along with re-sends of data, thereby slowing throughput. By reverting to a lower order modulation schemes the link can be made more reliable with fewer data errors and re-sends.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

30

3.4

QAM Applications

QAM is in many radio communications and data delivery applications. However some specific variants of QAM are used in some specific applications and standards.
For domestic broadcast applications for example, 64 QAM and 256 QAM are often used in digital cable television and cable modem applications. In the UK, 16 QAM and 64 QAM are currently used for digital terrestrial television using DVB - Digital Video Broadcasting. In the
US, 64 QAM and 256 QAM are the mandated modulation schemes for digital cable as standardized by the SCTE in the standard ANSI/SCTE 07 2000.
In addition to this, variants of QAM are also used for many wireless and cellular technology applications. PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

31

Chapter 4
METHODOLOGY

4.1

Pre-thesis Work

With the evolution of the wireless system the demand for high speed data services have been increasing day by day, which is impossible to be achieve by the conventional serial data transmission system without trade-off between high speed data services and QOS without increasing the band width of the system. Here both the options are inconvenient, as one never demands the degradation of the service quality (because if we increase data rate in serial data transmission ISI will gradually increase which make the extraction of actual information at receiver nearly impossible ) and secondly the need for extra spectrum in a limited spectrum scenario. In order to overcome this problem new parallel data transmission system was proposed, which is known as OFDM system.
We have decided to work about this new communication technology. Our first thinking was how we can improve the system performance of the OFDM communication system. Which channel will be efficient for OFDM system and by applying which modulation technique we can achieve the better performance for OFDM system was our main goal of the work.
The figure 4.1 shows the flowchart of our working procedure. Here each block represents the each step that we followed during the work.
At the starting of the work we have studied about the multicarrier transmission technique
OFDM. We tried to gather knowledge about the OFDM communication system. As efficiency of today’s communication need to be increased, so we have to be familiar with the OFDM communication system.
Than we tried to gather knowledge on different channels. Communicating from one location to another requires some form of pathway or medium. These pathways, called communication channels, use two types of media: cable (twisted-pair wire, cable, and fiber-optic cable) and broadcast (microwave, satellite, radio, and infrared). Cable or wire line media use physical wires

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32

of cables to transmit data and information. Twisted-pair wire and coaxial cables are made of copper, and fiber-optic cable is made of glass.

FIGURE 4.1: Flow chart of the working principle

We studied about different modulation technique. Their effect on different channel is very significant. PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

33

4.2

Work Done at Thesis

First of all we developed the system model of the OFDM communication system. The system model is consists of various parts.

FIGURE 4.2: System model of OFDM communication system [2].
The above figure shows the block diagram of OFDM communication systems system model. We developed the each block considering the performance of the individuals.
The ‘serial to parallel’ block is implemented because to compensate with overlapping subchannels and to avoid the use of high-speed equalization to combat impulsive noise and multipath distortion and fully utilize bandwidth.
The modulation block is used as we need to modulate the carrier frequency while transmitting.
And at the receiving end again we need to demodulate the signal. In our work, to compare and to find the suitable modulation technique for OFDM communication system we used four types of modulation techniques.
•

Binary phase shift-keying (BPSK)

•

Quadrature phase-shift keying (QPSK)

•

16-QAM

•

64-QAM

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

34

The IFFT and FFT [8] are used for modulating and demodulating individual OFDM sub-carriers to transform the signal spectrum to the time domain for transmission over the channel and then by employing FFT on the receiving end to recover data symbols in serial order.
The second key principle is the cyclic prefix (CP) as Guard Interval (GI). CP keeps the transmitted signal periodic. One of the reasons to apply CP is to avoid Inter Carrier Interference
(ICI).
The channel block represents the medium through which the communication will be established.
Channel refers either to a physical transmission medium such as a wire or to a logical connection over a multiplexed medium such as a radio channel. A channel is used to convey an information signal, for example a digital bit stream, from one or several senders (or transmitters) to one or several receivers. A channel has a certain capacity for transmitting information, often measured by its bandwidth in Hz or its data rate in bits per second.
For our research we used
•

Rayleigh fading channel

•

Rician fading channel

•

AWGN channel

Next we analyzed the performance of the OFDM system. The analysis was on the basis of bit error ratio vs. signal to noise ratio. We have used Matlab R2008a software for the simulation purpose. We considered different channel. We used different modulation technique for the analysis. At first we considered AWGN channel. For AWGN channel we used different modulation technique. We used BPSK, QPSK, 16-QAM, 64-QAM modulation techniques. For different modulation technique we got different response.
Similarly for Rayleigh and Rician channel, by using different modulation technique, we got different responses.
We also calculated the probability of error of OFDM system for different channel using different modulation technique.
At last we compared the data to determine the suitable channel and also the suitable modulation technique for OFDM communication system.
Thus we have accomplished our work.

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35

4.3

Simulation Procedure

To perform the simulation we have followed some procedure. We have done our work in an organized way. We followed the system model that we developed for drawing the simulation steps. We have done our simulation by using the software Matlab R2008a. It has some build in program that helps to simulate our program. We have done our work very carefully. First of all we declared the simulation parameters. We took the simulation parameter as it suits our work. It is necessary to select simulation parameter before doing the simulation work. Because, random and unorganized work may leads to a disaster.
The procedures that we have followed to develop the OFDM simulator is briefly stated as follows: At the transmission section:
•

At first we have generated a random data stream of length 3072 bit as our input binary data using Matlab R2008a. Then randomization process has been carried out to scramble the data in order to convert long sequences of 0's or 1's in a random sequence to improve the coding performance.

•

Secondly we have performed Cyclic Redundancy Check (CRC) encoding.

•

Then various digital modulation techniques, as specified namely BPSK, QPSK,
16-QAM and 64-QAM are used to modulate the encoded data.

•

The modulated data in the frequency domain is then converted into time domain data by performing IFFT on it.

•

For reducing inter-symbol interference (ISI) cyclic prefix has been added with the time domain data.

•

Finally the modulated parallel data were converted into serial data stream and transmitted through different communication channels.

•

Using Matlab built-in functions, “awgn”, “rayleighchan” and “ricianchan” we have generated AWGN, Rayleigh and Rician channels respectively.

At the receiving section we have just reversed the procedures that we have performed at the transmission section. After ensuring that the OFDM simulator is working properly we started to evaluate the performance of our developed system. For this purpose we have varied encoding

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

36

techniques and digital modulation schemes under AWGN and frequency-flat fading (Rayleigh/
Rician) channels. Bit Error Rate (BER) calculation against different Signal-to-Noise ratio (SNR) was adopted to evaluate the performance. We also adopted Probability Error P(e) calculation against different Signal-to-Noise ratio (SNR) to evaluate the performance.

4.4

Simulation Basis

Our work is to evaluate the performance of OFDM communication system for different channels and different modulation techniques. After evaluating we will compare the performance.
The performance of the OFDM communication system is on the basis of the ratio of bit error rate
(BER) vs. signal to noise ratio (SNR). We also evaluated the performance on the basis of probability error P(e) vs. SNR ratio.

A. Bit Error Rate (BER)
In digital transmission, the no. of bit errors is the number of receiving bits of a signal data over a communication channel that has been changed because of noise, noise, distortion, interference or bit synchronization redundancy. The bit error rate or bit error ratio (BER) is defined as the rate at which errors occur in a transmission system during a studied time interval. BER is a unit less quantity, often expressed as a percentage or 10 to the negative power. The definition of BER can be translated into a simple formula:
BER = Number of errors / Total number of bits sent
Noise is the main enemy of BER performance. Quantization errors also reduce BER performance, through unclear reconstruction of the digital waveform. The precision of the analog modulation/ demodulation process and the effects of filtering on signal and noise bandwidth also influence quantization errors.

B. Signal to Noise Ratio (SNR)
The SNR is the ratio of the received signal power over the noise power in the frequency range of the process. SNR is inversely related to BER, that is high BER causes low SNR. High BER causes an increase in packet loss, enhance in delay and decrease throughput. SNR is an indicator usually measures the clarity of the signal in a circuit or a wired/wireless transmission channel
PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

37

and measure in decibel (dB). Th SNR is the ratio between the wanted signal and the unwanted he la background noise.

SNR =

Psignal
Pnoise

SNR formula in terms of diversit sity: BER ∝

1
S d
SNR

C. Probability of Error P (e) or It is the measure of error of est stimate for a sample from a normal distribution It indicates the on. deviation from the normal distrib ribution to the present distribution.
In a binary PCM system, binary d y digits may be represented by two pulse levels. If these levels are
I
chosen to be 0 and A, the signal is termed an on-off binary signal. If the level switches between al ls
A=2 and A=2 it is called a polar binary signal. Suppose we are transmitting digital information, lar dig and decide to do this using two-le pulses each with period T: level The binary digit 0 is represented by a signal of level 0 for the duration T of the transmission, and ed t the digit 1 is represented by the signal level At. In what follows we do not con e onsider modulating the signal, it is transmitted at b baseband. In the event of a noisy Gaussian channel (with high cha bandwidth) the signal at the recei ceiver may look as follows:
Here the binary levels at the rece ceiver are nominally 0 (signal absent) and A (sign present) upon ignal receipt of a 0 or 1 digit respectiv ively. The function of a receiver is to distinguish the digit 0 from ish the digit 1. The most important p t performance characteristic of the receiver is the probability 1 that ep an error will be made in such a d determination. Consider the received signal wav aveform for the bit
PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE
YSTEM
TECHNIQU

38

transmitted between time 0 and time T. Due to the presence of noise the actual waveform y(t) at the receiver is

y (t ) = f (t ) + n(t )

(4.1)

Where f (t) is the ideal noise free signal. In the case described the signal f(t) is

f t =

0, symbol 0 transmitted Signal absent
1, symbol 0 transmitted Signal absent

In what follows, it is assumed that the transmitter and the receiver are synchronized, so the receiver has perfect knowledge of the arrival times of sequences of pulses. The means of achieving this synchronization is not considered here. This means that without loss of generality we can always assume that the bit to be received lays in the interval (0, T).
A very simple detector could be obtained by sampling the received signal at some time instant Ts in the range (0, T), and using the value to make a decision. The value obtained would be one of the following:

y (Ts ) = n (Ts )

Signal absent

y(Ts ) = A + n (Ts )

Signal present

Since the value n(T) is random, we cannot decide with certainty whether a signal was present or not at the time of the sample. However, a reasonable rule for the decision of whether a 0 or a 1 was received is the following:

y(T ) ≤ µ

Signal absent____0 received

y(T ) > µ

Signal present___1 received

The quantity μ is a threshold which we would usually choose somewhere between 0 and A. For convenience we denote y(Ts) by y.
Suppose now that n(Ts) has a Gaussian distribution with a mean of zero and a variance of σ2.
Under the assumption that a zero was received the probability density of y is

p0 ( y) =

2
2
1 e− y ⁄(2σ )
2π σ

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

(4.2)

39

Similarly, when a signal is presen the density of y is sent, p1 ( y) =

2
2
1 e−( y − A) ⁄(2σ )
2π σ

(4.3)

These are shown below:

Figure 4.3 Probability error observation curve [14].
.3:
Using the decision rule described it is evident that we sometimes decide that a signal is present bed, t even when it is in fact absent. Th probability of such a false alarm occurring (mistaking a zero
The
g( for a one) is

P0 =∫
∈

α

µ

1 e− y2 ⁄(2σ 2 )dy
2π σ

(4.4)

Similarly, the probability of a mi missed detection (mistaking a one for a zero) is

P =∫
∈1

µ

−α

1 e−( y − A)2 ⁄(2σ 2 ) dy
2π σ

(4.5)

Letting P0 and P1 be the source d digit probabilities of zeros and ones. Respectivel we can define vely, the overall probability of error to be

P = P0 P + P P
∈
∈0
1 ∈1

(4.6)

In the equiprobable case this beco ecomes P = 1 (P + P )
∈
∈0
∈1
2

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE
YSTEM
TECHNIQU

(4.7)

40

The sum of these two errors will be minimized for μ=A/2. This sets the decision threshold for a minimum probability of error for P0 = P1 = 1/2.
In that case the probabilities of each type of error are equal, so the overall probability of error is
∞

P = ∫A
∈
2

1 e− y2 ⁄(2σ2 )dy
2π σ

(4.8)

Making the change of variables z = y/σ this integral becomes

P =∫
∈

∞
A ⁄ (2σ )

= erfc(

1 e− z2 ⁄ 2dz
2π

A
)
2σ

(4.9)

A graph of Pϵ as a function of A/(2σ) can be found in Stremler. This may be written in a more

useful form by noting that the average signal power is S = A2/2, and the noise power is N = σ2.
The probability of error for on-off binary is therefore

P = erfc
∈

S
2N

(4.10)

The selection of voltages 0 and A may be difficult for baseband transmission, since an overall
DC current flow is implied. If instead a zero is represented by the voltage A/2 and a one by A/2, then the entire calculation can be repeated — the only difference is that now S = (A/2)2, so for polar binary

P = erfc
∈

S
N

(4.11)

The on-off binary signal therefore requires twice the signal power of the polar binary signal to achieve the same error rate.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

41

4.5

Simulation Model

This point discusses the simulation model used to represent the work that we done. The aim of the simulation was to study the system performance of OFDM under different channel conditions and using different modulation technique. The simulation is done by using Matlab R2008a. The simulation results obtained for different combinations of the system parameters will be discussed. Figure 4.4: Hierarchical representation of the m-files.

The above figure shows the hierarchical representation of matlab m-files. When we run awgn.m or rayleigh.m or rician.m than it calls the matlab functions as above.
At the transmitter section first we need to convert the serial data into parallel. So first it calls the serial2parallel.m function. Next to modulate the signal by different modulation techniques we need to call the ofdm_mapping.m function. To reduce the inter-symbol interference (ISI) we need to add cyclic prefix. So at that point we need to call the cyclicpad.m function.
At the receiver section we need to do the same thing in reverse direction.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

42

4.6

System Parameters

OFDM system parameters used in the simulation are indicated in Table 1. Moreover, we have chosen the guard interval to be greater than the maximum delay spread in order to avoid InterSymbol Interference. Simulations are carried out for different Signal-to Noise (SNR) ratios and for each value of the Bit Error Rate (BER) are calculated. The simulation parameters to achieve those results are shown in the Table 1.

Table 1: Simulation Parameter
Parameters

Specification

Number of Bits

3072

Number of Subscribers

512

FFT Size

512

CP

¼

K Factor

3

Maximum Doppler Shift

100 Hz

SNR

0-18

Modulation

BPSK, QPSK, 16-QAM, 64-QAM

Noise Channels

AWGN, Rayleigh, Rician

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

43

Chapter 5
Analysis of Simulation Result

5.1

Simulation Results and Discussions

This section of the chapter presents and discusses all of the results obtained by the computer simulation program written in Matlab R2008a, following the analytical approach of an OFDM communication system considering AWGN, Rayleigh Fading and Rician Fading channel. A test case is considered with the synthetically generated data. The results are represented in terms of bit energy to noise power spectral density ratio (SNR) and bit error rate (BER) for practical values of system parameters.
By varying SNR, the plot of SNR vs. BER was drawn with the help of “semilogy” function. The
Bit Error Rate (BER) plot obtained in the performance analysis showed that model works well on Signal to Noise Ratio (SNR) less than 20 dB. We analyzed the performance of the OFDM communication system on the basis of BER vs. SNR plot and also on the basis of P(e) vs. SNR plot. Simulation results in figure 5.2, figure 5.3 and figure 5.4 shows the performance of the system over AWGN and fading (Rayleigh & Rician) channels using BPSK, QPSK, 16-QAM and 64QAM modulation schemes respectively.
In figure 5.5, figure 5.6 and figure 5.7 shows the simulation result of Probability Error P (e) vs.
SNR over AWGN and fading (Rayleigh & Rician) channels using BPSK, QPSK, 16-QAM and
64-QAM modulation schemes respectively.
After that we have drawn the comparison table for AWGN and fading (Rayleigh & Rician) channels using BPSK, QPSK, 16-QAM and 64-QAM modulation schemes respectively.
Table 2 shows the comparison table of BPSK, QPSK, 16-QAM and 64-QAM over Rayleigh channel, Table 3 shows the comparison table of BPSK, QPSK, 16-QAM and 64-QAM over
Rician channel and Table 4 shows the comparison table of BPSK, QPSK, 16-QAM and 64-QAM over AWGN channel.
Through the comparison table we will try to simplify our output that we obtained from the thesis.

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44

We will put specific discussion under each simulation result.

5.1.1 Simulation Result on the Basis of BER vs. SNR Ratio
In this section we will discuss about the simulation result that we obtained from the plot of BER vs. SNR. The performance result of OFDM system by varying different channels and different modulation techniques will be explained here.
Performance of OFDM in rayleigh channel with different Modulation Technique

0

10

BPSK
QPSK
16-QAM
64-QAM
-1

10

-2

BER

10

-3

10

-4

10

-5

10

0

2

4

6

8

10

12

14

16

18

SNR (dB)

Figure 5.1: Bit error rate (BER) performance of Rayleigh channel using BPSK, QPSK, 16-QAM and 64-QAM

The above figure shows the bit error rate performance of Rayleigh channel using BPSK, QPSK,
16-QAM and 64-QAM modulation techniques. The effect of Rayleigh channel under different modulation techniques are discussed later.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

45

Performance of OFDM in rician channel with different Modulation Technique

0

10

BPSK
QPSK
16-QAM
64-QAM
-1

10

-2

BER

10

-3

10

-4

10

-5

10

0

2

4

6

8

10

12

14

SNR (dB)

Figure 5.2: Bit error rate (BER) performance of Rician channel using BPSK, QPSK, 16-QAM and 64-QAM

The above figure shows the bit error rate performance of Rician channel using BPSK, QPSK, 16QAM and 64-QAM modulation techniques. The effect of Rician channel under different modulation techniques are discussed later.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

46

Performance of OFDM in AWGN channel with different Modulation Technique

0

10

BPSK
QPSK
16-QAM
64-QAM
-1

10

-2

BER

10

-3

10

-4

10

-5

10

0

1

2

3

4

5
SNR (dB)

6

7

8

9

10

Figure 5.3: Bit error rate (BER) performance of AWGN channel using BPSK, QPSK, 16-QAM and 64-QAM

The above figure shows the bit error rate performance of AWGN channel using BPSK, QPSK,
16-QAM and 64-QAM modulation techniques. The effect of AWGN channel under different modulation techniques are discussed later.
A. Effect of Rayleigh, Rician and AWGN Channel on OFDM

Communication System
From Figure- 5.2, 5.3 and 5.4 we can see that, AWGN channel has lower BER than Raleigh and
Rician fading channel. For an example, while using the QAM modulation scheme, for 64-QAM, when SNR value is 9, BER for AWGN channel is 3.98e-03, where BER for Rayleigh and Rician channel remains 0.0316 and 0.0125 respectively. But Raleigh & Rician fading channel has more non-zero BER values than that of AWGN channel.
While using PSK modulation technique, for QPSK modulation scheme, when SNR value is 5,
BER for AWGN channel is 5.9118e-04, where BER for Rayleigh and Rician channel remains
0.0125 and 6.3095e-03 respectively.
PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

47

So from the above discussion we can say that, AWGN channel is more suitable than Rayleigh and Rician channel for OFDM communication system as AWGN channel has less BER than the others. After that, Rician channel is better than Rayleigh Channel as it has less BER than
Rayleigh channel.

B. Effect of BPSK, QPSK, 16-QAM and 64-QAM Modulation on OFDM

Communication System
The effect of different modulation techniques on OFDM communication system is different. For simplifying the simulation we have drawn three comparison tables that represent the performance of BPSK, QPSK, 16-QAM and 64-QAM modulation technique over OFDM communication system. From the table we can easily explain the performance of different modulation technique over OFDM communication system.
Here we showed response of different modulation scheme on the basis of BER vs. SNR ratio.
For different SNR value the BER rate is shown.
Table 2: Comparison Table for Rayleigh Channel Using Different Modulation Technique

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

48

Table 3: Comparison Table for Rician Channel Using Different Modulation Technique

Table 4: Comparison Table for AWGN Channel Using Different Modulation Technique

From table 2, 3 and 4 we can see that BER increases as modulation level increases. The reason for this is that as modulation level increases amplitude and phase spacing between adjacent symbol decreases. Because of this, same noise produces greater error than that of smaller modulation level. The same result occurs for PSK where amplitude and frequency remains constant and only phase changes. As modulation level increases, phase spacing between adjacent symbols decreases which causes greater error.
Through all of the tables we analyzed that the BPSK modulation gives the least bit error rate, means it is an effective method for data transmission in all of the modulations and for all the channels in terms of bit error rate. As for example BPSK at the BER value of 10-4 we get SNR value of 4.9 dB for AWGN channel in table 4, 6.7 dB for Rician channel in table 3 and 8.3 dB for Rayleigh channel in table 2. While for QPSK it is 5.6 dB, 7.8 dB and 9.4 dB, for 16-QAM it
PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

49

is 6.8 dB, 9.2 dB and 11.7 dB, for 64-QAM it is 9.7 dB, 13 dB and 16 dB respectively. That is for getting same BER we need to provide more signal power for QPSK, 16-QAM and 64-QAM.

5.1.2 Simulation Result on the Basis of P (e) vs. SNR Ratio
In this section we will discuss about the simulation result that we obtained from the plot of P(e) vs. SNR. The performance result of OFDM system by varying different channels and different modulation techniques will be explained here.

Probability Error Observation for rayleigh channel

1

10

BPSK
QPSK
16-QAM
64-QAM

0

10

-1

10

-2

P (e)

10

-3

10

-4

10

-5

10

-6

10

0

5

10

15

20

25

SNR (dB)

Figure 5.4: Probability of Error P(e) performance of Rayleigh channel using BPSK, QPSK,
16-QAM and 64-QAM

The above figure shows the probability of error rate performance of Rayleigh channel using
BPSK, QPSK, 16-QAM and 64-QAM modulation techniques. The effect of AWGN channel under different modulation techniques are discussed later.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

50

Probability Error Observation for rician channel

1

10

BPSK
QPSK
16-QAM
64-QAM

0

10

-1

10

-2

P (e)

10

-3

10

-4

10

-5

10

-6

10

0

2

4

6

8

10

12

14

16

18

SNR (dB)

Figure 5.5: Probability of Error P(e) performance of Rician channel using BPSK, QPSK,
16-QAM and 64-QAM

The above figure shows the probability of error rate performance of Rician channel using BPSK,
QPSK, 16-QAM and 64-QAM modulation techniques. The effect of AWGN channel under different modulation techniques are discussed later.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

51

Probability Error Observation for awgn channel

1

10

BPSK
QPSK
16-QAM
64-QAM

0

10

-1

10

-2

P (e)

10

-3

10

-4

10

-5

10

-6

10

0

2

4

6

8

10

12

14

SNR (dB)

Figure 5.6: Probability of Error P(e) performance of AWGN channel using BPSK, QPSK,
16-QAM and 64-QAM

The above figure shows the probability of error rate performance of AWGN channel using
BPSK, QPSK, 16-QAM and 64-QAM modulation techniques. The effect of AWGN channel under different modulation techniques are discussed later.

A. Effect of Rayleigh, Rician and AWGN Channel on OFDM

Communication System
The effect of different channel on OFDM communication system is different. For simplifying the simulation we have drawn three comparison tables that represent the performance of Rayleigh,
Rician and AWGN channel over OFDM communication system. From the table we can easily explain the performance of different channel over OFDM communication system.
Here we showed the response of different channel scheme on the basis of P(e) vs. SNR ratio.

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

52

Table 5: Comparison Table for Rayleigh Channel Using Different Modulation Technique

Table 6: Comparison Table for Rician Channel Using Different Modulation Technique

Table 7: Comparison Table for AWGN Channel Using Different Modulation Technique

PERFORMANCE EVALUATION OF OFDM SYSTEM FOR DIFFERENT CHANNEL AND DIFFERENT MODULATION TECHNIQUE

53

From Table 5, 6 and 7 we can see that, AWGN channel has lower P(e) than Rayleigh and Rician fading channel. For an example, while using the QAM modulation scheme, for 64-QAM, when
SNR value is 10, P(e) for AWGN channel is 0.398, where P(e) for Rayleigh and Rician channel remains 0.631 and 0.501 respectively.
While using PSK modulation technique, for QPSK modulation scheme, when SNR value is 10,
P(e) for AWGN channel is 2.511e-03, where P(e) for Rayleigh and Rician channel remains
0.012 and 0.01 respectively.

So from the above discussion we can say that, AWGN channel is more suitable than Rayleigh and Rician channel for OFDM communication system. As AWGN channel has less P(e) than the others. After that, Rician channel is better than Rayleigh Channel as it has less P(e) than
Rayleigh channel.

B. Effect of BPSK, QPSK, 16-QAM and 64-QAM Modulation on OFDM

Communication System
From table 5, 6 and 7 we can see that P(e) increases as modulation level increases. From the tables we analyzed that the BPSK modulation gives the least probability error, means it is an effective method for data transmission in all of the modulations and for all the channels in terms of probability error.
As for example BPSK at the SNR value of 8 we get P(e) value of 1.99e-04 for AWGN channel in table 7, 1.258e-03for Rician channel in table 6 and 1.584e-03 for Rayleigh channel in table 5.
While for QPSK it is 0.01, 0.0158 and 0.0199, for 16-QAM it is 0.1, 0.125 and 0.158, for 64QAM it is 0.501, 0.631 and 0.794 respectively.

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Chapter 6
Conclusion & Future Work

6.1

Conclusion

The current status of the research is that OFDM appears to be a suitable technique as a modulation technique for high performance wireless telecommunications. In this research work, it has been studied the performance of an OFDM Communication system for different channel and different modulation scheme. A range of system performance results highlights the impact of
AWGN and fading (Rayleigh & Rician) channels under BPSK, QPSK, 16-QAM & 64-QAM modulation techniques. From this research work, conclusions can be drawn regarding the BER performance evaluation of OFDM Communication system over AWGN channel and fading
(Rayleigh & Rician) channels. We also evaluate the probability error performance of OFDM
Communication system over AWGN channel and fading (Rayleigh & Rician) channels.
From our research we found that, Performance of OFDM-based systems are almost similar to theory. The conclusion can be drawn as follows:
The performance of AWGN channel is the best of all channels as it has the lowest bit error rate (BER) & lowest probability error P(e) under all modulation schemes. The amount of noise occurs in the BER of this channel is quite slighter than fading channels.
The performance of Rayleigh fading channel is the worst of all channels as BER & P(e) of this channel has been much affected by noise under BPSK, QPSK, 16-QAM & 64QAM modulation schemes.
The performance of Rician fading channel is worse than that of AWGN channel and better than that of Rayleigh fading channel. Because Rician fading channel has higher
BER & P(e) than AWGN channel and lower than Rayleigh fading channel. BER of this channel has not been much affected by noise under BPSK, QPSK, 16-QAM & 64-QAM modulation schemes.
The change in P(e) vs. SNR with respect to modulation level is linear.

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Both BER & P(e) increases as modulation level increases.
As modulation level increases amplitude and phase spacing between adjacent symbol decreases. Because of this, same noise produces greater error than that of smaller modulation level.
Among all the modulation techniques, BPSK shows the lowest BER & P(e).
So we can say that, among BPSK, QPSK, 16-QAM & 64-QAM, BPSK is most suitable modulation technique for OFDM system.

6.2

Future Work

Research can be done to illustrate the effect of the delay spread, peak power clipping etc. In this simulation no multi-path fading reduction techniques have been simulated and this is a field of future work also. One important major area which hasn’t been investigated is the problems that may be uncounted when OFDM is used in a multi-user environment. One possible problem which may be encountered is the receiver may require a very large dynamic range in order to handle the large signal strength variation between users. Several modulation techniques for
OFDM were investigated in this paper including BPSK, QPSK, 16-QAM and 64-QAM, however possible system performance gains may be possible by dynamically choosing the modulation technique based on the type of data being transmitted. More work could be done on investigating suitable techniques for doing this. OFDM promises to be a suitable modulation technique for high capacity wireless communications and will become more important in the future as wireless networks become more relied on.

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