实验：OFDM原理与实现
                   
一、实验内容
学习CP-OFDM实现代码
• 实现CP-SCFDE
• 实现ZP-OFDM
• 实现ZP-SCFDE
• 比较分析四种技术的识码率性能
• 分析ZP-OFDM/SCFDE两种方案的复杂度
• 探讨是否有降低ZP-OFDM与ZP-SCFDE均衡复杂
的可能性（选做）
1、学习CP-OFDM实现代码
（1）代码
N    = 256;    % 载波数, i.e., fft size
Ncp= N/4;      % 循环前缀的长度
Ns  = N + Ncp;  %每个OFDM符号的整个长度
Ntry = 100;    % OFDM帧的数量
Nsyb =  20;    % 每帧的OFDM符号的数目
M    = 16;        %M-ary QAM
m    = log2(M);    % m bits per subcarrier
Pav = 2*(M-1)/3.0;  % 每个子载波的平均功率
modulatePavdB = 10*log10(Pav/N);% 时间信号的分贝平均值
SNRdB = [0:5:40];        % SNR list to be simulated
% Set multi-path fading channel parameters
Np = Ncp/4;    % The number of multipaths
% idxTaps = sort(randperm(Ncp,Np));% After matlab 2012a
idxTaps = randperm(Ncp);        % before matlab 2012a
idxTaps = sort(idxTaps(1:Np));  % before matlab 2012a
idxTaps - idxTaps(1)+1; % Move the first multipath to 0 delay
DPS = exp(-3*idxTaps/Ncp);% power in each tap: Delay Power Spectrum
DPS = DPS/sum(DPS);            % Normalize
Ampath = sqrt(DPS);            % Amplitude of each path
%% Directly use Matlab channel object
% SymbolRate = 20e6;            % Sampling Rate
% Ts    = 1/SymbolRate;        % Symbol period
% Tau = (idxTaps-1)* Ts;  % tap delay in s
% PdB = 10*log10(DPS);      % Delay Power Spectrum in dB
% Fdop = 0;                                % Quasi-static channels
% ch  = rayleighchan(Ts, Fdop, Tau, PdB);
% ch.StorePathGains = 1;    % Flag to store path gain
hzero = zeros(Ncp,1);      % zero vector for channel impulse response
ErrSymbols = zeros(size(SNRdB)); %  store the number of the error symbols
tic                                                % the instant begin simulation
for numSimSymbols = 1 : Ntry
    curErrSymbols = 0;
    % Step 1: Generate random digital message
    d = randi([0,M-1],N,Nsyb); % Message signal
    % Step 2: M-QAM modulation.
    X = qammod(d,M);
    % Step 3: IFFT, generate time field signal,
    % i.e., modulate at frequency Field,
    x = ifft(X);       
    % Step 4: Ìí¼ÓÑ­»·Ç°×º
    xcp = [x(N-Ncp+1:end,:);x]; 
    % Serialize
    xcp = xcp(:);
    % Step 5a: Transmit through Channel
    % Mannully Generate multipath channel impulse response
        cir = Ampath.* ( randn(1,Np) + 1j*randn(1,Np))/sqrt(2);
        h = hzero; h(idxTaps) = cir.'; % store channel
        % Channel effect
        xcpch = zeros(Ns *Nsyb+Ncp,1);
        for p = 1:Np
            idx = [0:Ns *Nsyb-1]+idxTaps(p);
            xcpch(idx) = xcpch(idx) +  cir(p)*xcp;               
        end
        xcpch = xcpch(1:Ns *Nsyb);
    % Can also use Matlab chanel object
    % xcpch    = filter(ch, xcp);
    % h = hzero; h(idxTaps) = ch.PathGains;% Save channel
       
    for k=1:length(SNRdB)
        % Step 5b: AWGN
        y = awgn(xcpch,SNRdB(k),'measured');%PavdB);
       
        % Step 6: Delete CP
        y = reshape(y,[Ns,Nsyb]);
        y = y([Ncp+1:end],:);
      % Step 7:  FFT, Come back to Frequency Field
        Y    = fft(y);
        % Step 8: Frequency domain equalization
        HCP  = fft(h,N);% Channel Frequency Response of Prefect channel
        Gzf  = 1./HCP; % Zero-Forcing Equalizer
        Xhat= Y .* repmat(Gzf,[1,Nsyb]);
        % Step 9: Demodulate, to recover the message.
        dhat      = qamdemod(Xhat,M);
        % Step 10: Compute symbol error rate.
        ddif  = d - dhat; ddif =  ddif(:);
        curErrSymbols = length(find(ddif~= 0));
        ErrSymbols(k) = ErrSymbols(k) + curErrSymbols;
    end
end
toc  %simulation time
% Step 10: Show simulation results
cpSER =  ErrSymbols / (N*Nsyb*Ntry);
% Theory SER of M-ary QAM in flat Fading Channel
SNR  = 10.^(SNRdB/10);
EbNo =10*log10(SNR/m);
[thyBER,thySER]  = berfading(EbNo,'qam',M,1)
figure; semilogy(SNRdB, [cpSER;thySER],'-o');
xlabel('SNRdB'); ylabel('Symbol error ratio (SER)');
legend('Simulated CP-OFDM in multipath fading','Theoretical M-QAM in flat fading');grid on;
（2）结果
（3）分析

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