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基于matlab模拟OFDM中SNR和BER的关系附完整代码

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⛄ 内容介绍

The proliferation of mobile platforms has put lot of stress in terms of power limitations and Quality of Service being offered by OFDM systems. BER and SNR analysis plays an important and imperative role in understanding and improving the design of OFDM systems. In this paper we have presented a comprehensive analysis about BER and SNR for various scenarios which include different channels, different modulation techniques and carrier frequency offsets.

⛄完整代码

clc;

clear all;

close all;


%% Initializing parameters

L=input('Length Of OFDM Data = ');

Ncp=L*0.0625

%% Transmitter



% data generation

Tx_data=randi([0 15],L,Ncp);

%%%%%%%%%%%%%%%%%%% QAM modulation %%%%%%%%%%%%%%%%%%%%%

mod_data=qammod(Tx_data,16);

% Serial to Parallel

s2p=mod_data.';

% IFFT

am=ifft(s2p);

% Parallel to series

p2s=am.';

% Cyclic Prefixing

CP_part=p2s(:,end-Ncp+1:end); %Cyclic Prefix part to be appended.

cp=[CP_part p2s];


%%  Reciever


% Adding Noise using AWGN

SNRstart=0;

SNRincrement=1;

SNRend=25;

c=0;

r=zeros(size(SNRstart:SNRincrement:SNRend));

for snr=SNRstart:SNRincrement:SNRend

    c=c+1;

    noisy=awgn(cp,snr,'measured');

% Remove cyclic prefix part

    cpr=noisy(:,Ncp+1:Ncp+Ncp); %remove the Cyclic prefix

% series to parallel

    parallel=cpr.';

% FFT

    amdemod=fft(parallel);

% Parallel to serial

    rserial=amdemod.';

%%%%%%%%%%%%%%%%%%%% QAM demodulation %%%%%%%%%%%%%%%%%%%%%

    Umap=qamdemod(rserial,16);

% Calculating the Bit Error Rate

    [n, r(c)]=biterr(Tx_data,Umap);


end

snr=SNRstart:SNRincrement:SNRend;

%% Plotting BER vs SNR

semilogy(snr,r,'-ok');

grid;

title('OFDM Bit Error Rate .VS. Signal To Noise Ratio');

ylabel('BER');

xlabel('SNR [dB]');

⛄ 运行结果

基于matlab模拟OFDM中SNR和BER的关系附完整代码_无人机

⛄ 参考文献

[1] Mr. S V ,  Siddaiah. P . Comprehensive Analysis of BER and SNR in OFDM Systems.  1970.

⛄ 完整代码

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