21444658 Multi User Detection in Cdma Project Report

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    A SEMINAR REPORT ON

    MULTI-USER DETECTION IN CDMA

    Submitted in partial fulfillment of the requirements

    for the award of the degree of

    Bachelor of Technology

    In

    Electronics & Communication Engineering

    Guide: Submitted by:

    Mrs. PINKI NAYAK TARUN KUMAR

    Roll No.: 0111042805

    Amity School of Engineering & Technology

    Guru Gobind Singh Indraprastha University (GGSIPU), Delhi

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    ACKNOWLEDGEMENT

    I am thankful to my guide Mrs. Pinki Nayak for her support in collection and compilation of data

    and providing guidance to use and analyze the data for seminar matter.

    I also thank my parents and my family for their moral support to carry out the seminar report work.

    TARUN KUMAR

    DATE:

    PLACE:

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    ABSTRACT

    One of the major issues in present wireless communications is how users share the resources and

    particularly, how they access to a common frequency band. Code Division Multiple Access (CDMA) is

    one of the techniques exploited in third generation communications systems and is to be employed in the

    next generation. In CDMA each user uses direct sequence spread spectrum (DS-SS) to modulate its bits

    with an assigned code, spreading them over the entire frequency band. While typical receivers deal only

    with interferences and noise intrinsic to the channel (i.e. Inter-Symbolic Interference, intermodulation

    products, spurious frequencies, and thermal noise), in CDMA we also have interference produced by other

    users accessing the channel at the same time. Interference limitation due to the simultaneous access of

    multiple users systems has been the stimulus to the development of a powerful family of Signal

    Processing techniques, namely Multi-user Detection (MUD).

    These techniques have been extensively applied to CDMA systems. Thus, most of last generation digital

    communication systems such as Global Positioning System (GPS), wireless 802.11b, Universal Mobile

    Telecommunication System (UMTS), etc, may take advantage of any improvement on this topic. In

    CDMA, we face the retrieval of a given user, the User of Interest (UOI), with the knowledge of its

    associated code or even the whole set of users codes. Hence, we face the suppression of interference due

    to others users. If all users transmit with the same power, but the UOI is far from the receiver, most users

    reach the receiver with larger amplitude, making it more difficult to detect the bits of the UOI. This is

    well-known as the near-far problem. Simple detectors can be designed by minimizing the Mean Square

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    Error (MMSE) to linearly retrieve the user of interest. However, these detectors need large sequences of

    training data. Besides, the optimal solution is known to be nonlinear.

    There have been several attempts to solve the problem using nonlinear techniques. There are solutions

    based on Neural Networks such as multilayer perceptron or radial basis functions but training times are

    long and unpredictable. Recently, support vector machines (SVM) have been also applied to CDMA

    MUD. The upcoming third generation mobile radio system in Europe is based on UMTS (Universal

    Mobile Telecommunications Standard). In order to supply access to a common transmission channel for

    several users, UMTS incorporates Code Division Multiple Access (CDMA). Besides a lot of practical

    advantages, CDMA suffers from multi- user interference limiting spectral efficiency dramatically.

    However, bandwidth is a very valuable resource and should be used as efficiently as possible. One

    appropriate mean to increase spectral efficiency of CDMA systems is multi- user detection.This report gives an overview of different multi- user detection techniques. Their performance is

    compared with the conventional single-user detection including channel coding. Specifically, linear as

    well as nonlinear multi- user detectors are considered. Efficient realizations of linear detectors are given

    leading to improved nonlinear techniques. It is shown that nonlinear MUD including channel decoding

    can achieve a spectral efficiency twice as high as that of the well-known GSM standard (Global System

    for Mobile Communications) employing TDMA and FDMA.

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    TABLE OF CONTENTS

    _________________________ ___________________________________________________________ __________________________________

    CERTIFICATE ii

    ACKNOWLEDGEMENT iii

    ABSTRACT iv

    LIST OF FIGURES 6

    1. INTODUCTION

    1.1 Synchronous CDMA 9

    1.2 Asynchronous CDMA 10

    2. PRACTICAL CDMA RECIEVER

    2.1. Description 11

    2.2 Perfect power control 12

    2.3 Near far effect in CDMA 13

    3. CDMA COMMUNICATION SYSTEM MODEL AND MUD

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    3.1 Multiple access interference (MAI) 16

    3.2 MAI versus Intersymbol interference (ISI) 16

    4. MAXIMUM LIKELIHOOD SEQUENCE DETECTION

    4.3 Basic concept 18

    4.4 Formulation 18

    5. CONVENTIONAL DETECTION FOR MULTIPLE ACCESSES

    5.1 Output of the kth user 19

    5.2 Matrix Notation 19

    5.3 Data term and MAI term 20

    6. SYNCHRONOUS AND ASYNCHRONOUS CHANNEL

    6.1 Channel correlation matrix 21

    6.2 Decorrelating detector 22

    6.3 Polynomial expansion detectors 22

    7. MINIMUM MEAN SQUARE ERROR (MMSE) DETECTION 24

    8. SUCCESSIVE INTERFERENCE CANCELLATION (SIC) 25

    9. PARALLEL INTERFERENCE CANCELLATION (PIC)

    9.1 PIC properties 26

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    10. BENEFITS AND LIMITATION OF MULTIUSER

    DETECTION (MUD) 28

    CONCLUSION AND FUTURE WORK 29

    REFERENCES 30

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    LIST OF FIGURES

    Chapter - 1

    Fig. 1.1 Asynchronous CDMA 9

    Chapter - 2

    Fig. 2.1 Practical CDMA receivers 11

    Fig. 2.2 AWGN vs. Users graph 12

    Chapter - 3

    Fig. 3.1 CDMA communication system model 16

    Chapter 5

    Fig 5.1 Conventional detection for multiple accesses 19

    Chapter 6

    Fig 6.1 Asynchronous and Synchronous channel 22

    Chapter 8

    Fig 8.1 SIC block diagram 25

    Chapter 9

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    Fig 9.1 PIC block diagram 26

    CHAPTER-1 INTRODUCTION

    In addition to intersymbol and interchip interference, one of the key obstacles to signal detection and

    separation in CDMA systems is the detrimental effect of multi-user interference (MUI) on the

    performance of the receivers and the overall communication system. Compared to the conventional

    single-user detectors where interfering users are modeled as noise, significant improvement can be

    obtained with multi-user detectors where MUI is explicitly part of the signal model .if the spreading

    sequences are periodic and repeat every information symbol, the system is referred to as short-code

    CDMA, and if the spreading sequences are aperiodic or essentially pseudorandom, it is known as long-

    code CDMA. Since multi-user detection relies on the cyclostationarity of the received signal, which is

    significantly complicated by the time-varying nature of the long-code system, research on multi-user

    detection has largely been limited to short-code CDMA for some time. On the other hand, due to its

    robustness and performance stability in frequency fading environment, long code is widely used in

    virtually all operational and commercially proposed CDMA systems, as shown in Figure 1. Actually,

    each users signal is first spread using a code sequence spanning over just one symbol or multiple

    symbols. The spread signal is then further scrambled using a long-periodicity pseudorandom sequence.

    This is equivalent to the use of an aperiodic(long) coding sequence as in long-code CDMA system, and

    the chip-rate sampled signal and MUIs are generally modeled as time-varying vector processes. The

    time-varying nature of the received signal model in the long-code case severely complicates the

    equalizer development approaches, since consistent estimation of the needed signal statistics cannot be

    achieved by time-averaging over the received data record.

    More recently, both training-based and blind multi-user detection methods targeted at the long-codeCDMA systems have been proposed. In this paper, we will focus on blind channel estimation and user

    separation for long-code CDMA systems.

    Based on the channel model, most existing blind algorithms can roughly be divided into three classes.

    (i) Symbol-by-symbol approaches. As in long-code systems, each users spreading code changes

    for every information symbol, symbol-by-symbol approaches process each received symbol

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    individually based on the assumption that channel is invariant in each symbol. Channel

    est