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    ELEG 6913

    DIGITAL COMMUNICATION OVER FADING CHANNEL

    Project 2 Report

    STUDENT NAME:

    PATEL, KIRTIKUMAR. MODI, BHUVAN

    SUBMITTED TO:

    Annamalai, Annamalai Jr., Ph.D

    Associate Professor

    Department of Electrical and Computer Engineering

    Prairie View A&M University

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    Topic: Throughput Optimization Using Adaptive Techniques

    Objective: Maximization of single user throughput in a wireless channel

    using the symbol rate, Packet length, and the constellation

    size of MQAM modulation as optimization variables.

    Introduction:Throughput is defined as the number of bits per second correctly received. It can

    be affected by various by the channel environment such as the distance between

    transmitter and receiver, the fading state of the channel, and the noise and the

    interference power characteristics. After carefully reviewing [1] and [2] we came to know

    that symbol rate, Packet length, and the constellation size are SNR dependent and can

    be adapted dynamically in response to the mobility of a wireless data terminal.

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    0 2 4 6 8 10 12 14 16 18 200

    1000

    2000

    3000

    4000

    5000

    6000

    7000

    8000

    9000

    10000

    Received SNR(dB)

    SpectralEfficiency(bps/Hz)

    AWGN

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    -10 -5 0 5 10 15 20 25 300

    1

    2

    3

    4

    5

    6

    7

    8

    Received SNR(dB)

    SpectralEfficiency(bps/Hz)

    QPSK

    BPSK

    16 QAM

    64 QAM

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    -10 -5 0 5 10 15 20 25 300

    0.5

    1

    1.5

    2

    2.5

    3

    Received SNR(dB)

    SpectralEfficiency(bps/Hz)

    L = 256

    L = 64

    L = 32

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    -10 -5 0 5 10 15 20 25 300

    0.5

    1

    1.5

    2

    2.5

    3

    Received SNR(dB)

    SpectralEfficiency(bps/Hz)

    R = 125KHz

    R = 250 KHz

    R = 500 KHz

    R = 1 MHz

    close all;

    clear all;

    Eb = -10:1:30;

    SNR = 10.^(Eb/10);

    b = 2;

    Rs = 1000000;

    L = 100;

    C = 16;

    W = 10^6;

    Ls = L/b;

    for m = 1:length(SNR)

    x = sqrt((3*SNR)/(2^b-1));

    y = 4*(1-2^(-b/2));

    P = y*qfunc(x); % Equation (6)

    f = (1-P).^Ls; % Equation (4)T = ((L-C)/L)*b*Rs*f; % Equation (1)

    Z = (4*b*C)./log(1-P);

    L1 = C/2 + 0.5.*(sqrt(C*C)-Z); % Equation (9)

    T1=T/W; % Throughput in Bps/Hz

    end

    figure(1)

    plot(Eb,T1,'r+-');

    hold on;

    xlabel('Received SNR(dB)'),ylabel('Spectral Efficiency(bps/Hz)')

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    axis([-10 30 0 3]);

    grid On;

    %figure(2)

    %plot(Es,z,'r+-');

    %plot(Eb,L1,'r+-');

    %xlabel('Received SNR(dB)'),ylabel('Spectral Efficiency(bps/Hz)')

    %grid On;

    %hold on;

    %figure(3)

    %plot(Es,z,'r+-');

    %plot(Eb,Y,'r+-');

    %xlabel('Received SNR(dB)'),ylabel('Spectral Efficiency(bps/Hz)')

    grid on;

    hold on;

    References:

    [1] T. Yoo, R. J. Lavery, A. Goldsmith and D. J. Goodman, ThroughputOptimization UsingAdaptive Techniques, submitted to ICC2004.[2] T. Yoo, R. J. Lavery, A. Goldsmith and D. J. Goodman, ThroughputOptimization UsingAdaptive Techniques, Draft submitted to IEEE Communications Letters,

    2005.