从零开始学可见光通信，从开始到绝望…………………………

几点说明。

1. 一般在仿真的时候，大家都喜欢直接做等效基带仿真(类似于星座点的仿真)。

但实际要传，还是要传频带的波形信号。

2. 为了模拟真实的环境，先把基带信号经过一个自定义的信道，然后再做脉冲成型，上变频，加一点噪声AWGN进去。

3. 为了模拟同步，应该用专用的同步算法。但是这里的重点不在同步。所以用了很简单粗暴的办法。假装直接同步上了。

4. 为了造出不同步的结果，可以这样写 x_未同步 = [x(300:end); x; x]; 相当于循环发送，循环接收。

这是仿真。

Main

%%

% 单载波QPSK 接收端

% 2017年5月17日18:02:56

clear;

close all;

clc

rand_seed = 0;

rand('seed',rand_seed);

randn('seed',rand_seed);

%%

% Set up parameters and signals.

M = 4; % Alphabet size for modulation

baud_rate = 100; % Baud rate

f_carrier1 = 75; % Carrier frequency

Nsym = 10000; % Number of symbols

msg = randi([0 M-1],Nsym,1); % Random message

hMod = comm.RectangularQAMModulator(M);

modmsg = step(hMod,msg); % Modulate using QAM. % 映射后的基带信号

trainlen = 1000; % Length of training sequence

rolloff = .3; % 滚降因子

span = 20 ; % 截断长度

sps = 10;  % Samples per symbol

rrcFilter=rcosdesign(rolloff,span,sps,'sqrt'); %根升余弦滚降滤波器，‘sqrt’均方根升余弦；‘normal’升余弦

fs = baud_rate*sps; % 时间采样率,时间采样间隔为 1/fs 秒

Tsymbol=1/baud_rate;

% 2. 脉冲成型

% txSig = upfirdn(modmsg, rrcFilter, sps);  % 发送端的基带复波形信号

% chan = [1; .001];

chan = [.986; .845; .237; .123+.31i]; % Channel coefficients

% chan = [1 0.45 0.3+0.2i]; % Channel coefficients

filtmsg = filter(chan,1,modmsg); % Introduce channel distortion.(已经经过信道的畸变的基带复信号，星座点)

txSig = upfirdn(filtmsg, rrcFilter, sps);  % 发送端的基带复波形信号

txSig = awgn(txSig,20,'measured'); % Add AWGN

t = (0:1/fs:((length(txSig)-1)/fs)).';

T = t(end)+1/fs;

df = 1/T;

freq = -fs/2:df:fs/2-df;

cos1 = cos(2*pi*f_carrier1 * t);

sin1 = sin(2*pi*f_carrier1 * t);

x_upconv = real(txSig).* cos1 + imag(txSig) .* sin1;

%% === 接收端

x_training_wave = x_upconv;

x_training_msg = msg;

rxSig = [x_upconv(300:end) ; x_upconv];

% 1. 同步

x_resampled = resample(rxSig,1,1);

x_sync = sync_two_signals( x_resampled,x_training_wave,0);

figure(2);

plot(freq,20*log10(abs(fftshift(fft(x_sync))/max(abs(fftshift(fft(x_sync)))))));

ylim([-100,10])

xlim([0,freq(end)])

grid on;

xlabel('频率(Hz)');

title('接收信号');

% 2. 下变频 + 匹配滤波

xi_dnconv = x_sync .* cos1;

xq_dnconv = x_sync .* sin1;

x_filtered = xi_dnconv + 1j * xq_dnconv;

rxFilt = upfirdn(x_filtered, rrcFilter, 1, sps);

rxFilt = rxFilt(span+1:end-span); % 这是接收端匹配滤波后的信号

% 3. 均衡

% eq1 = lineareq(6, lms(0.01)); % LMS

eq1 = lineareq(30, rls(0.99,0.01)); % Create an equalizer object. % 40 taps，RLS算法，步长0.99，自相关矩阵逆矩阵的初值InvCorrInit对角线上的元素

eq1.SigConst = step(hMod,(0:M-1)')'; % Set signal constellation. % 标准星座图

[symbolest,~] = equalize(eq1,rxFilt,x_training_msg(1:trainlen)); % Equalize. % 均衡器obj，需要均衡的信号，训练序列

symbolest = symbolest ./ mean(abs(symbolest)) .* mean(abs(eq1.SigConst));

% Plot signals.

h = scatterplot(rxFilt,1,trainlen,'bx'); hold on;

scatterplot(symbolest,1,trainlen,'r.',h);

scatterplot(eq1.SigConst,1,0,'k*',h);

legend('Filtered signal','Equalized signal',...

'Ideal signal constellation');

hold off;

% Compute error rates with equalization.

hDemod = comm.RectangularQAMDemodulator(M);

demodmsg = step(hDemod,symbolest); % Demodulate detected signal from equalizer.

% Create ErrorRate Calculator System object

serVec = step(comm.ErrorRate,msg(trainlen+1:end),demodmsg(trainlen+1:end));

srate = serVec(1)

snum = serVec(2)

% Convert integers to bits

hIntToBit = comm.IntegerToBit(log2(M));

Tx_bit = step(hIntToBit, msg(trainlen+1:end));

Rx_bit = step(hIntToBit, demodmsg(trainlen+1:end));

% Calculate BER

berVec = step(comm.ErrorRate,Rx_bit,Tx_bit);

brate = berVec(1)

bnum = berVec(2)

%%

% 单载波QPSK 接收端

% 2017年5月17日18:02:56

clear;

close all;

clc

rand_seed = 0;

rand('seed',rand_seed);

randn('seed',rand_seed);

%%

% Set up parameters and signals.

M = 4; % Alphabet size for modulation

baud_rate = 100; % Baud rate

f_carrier1 = 75; % Carrier frequency

Nsym = 10000; % Number of symbols

msg = randi([0 M-1],Nsym,1); % Random message

hMod = comm.RectangularQAMModulator(M);

modmsg = step(hMod,msg); % Modulate using QAM. % 映射后的基带信号

trainlen = 1000; % Length of training sequence

rolloff = .3; % 滚降因子

span = 20 ; % 截断长度

sps = 10; % Samples per symbol

rrcFilter=rcosdesign(rolloff,span,sps,'sqrt'); %根升余弦滚降滤波器，‘sqrt’均方根升余弦；‘normal’升余弦

fs = baud_rate*sps; % 时间采样率,时间采样间隔为 1/fs 秒

Tsymbol=1/baud_rate;

% 2. 脉冲成型

% txSig = upfirdn(modmsg, rrcFilter, sps); % 发送端的基带复波形信号

% chan = [1; .001];

chan = [.986; .845; .237; .123+.31i]; % Channel coefficients

% chan = [1 0.45 0.3+0.2i]; % Channel coefficients

filtmsg = filter(chan,1,modmsg); % Introduce channel distortion.(已经经过信道的畸变的基带复信号，星座点)

txSig = upfirdn(filtmsg, rrcFilter, sps); % 发送端的基带复波形信号

txSig = awgn(txSig,20,'measured'); % Add AWGN

t = (0:1/fs:((length(txSig)-1)/fs)).';

T = t(end)+1/fs;

df = 1/T;

freq = -fs/2:df:fs/2-df;

cos1 = cos(2*pi*f_carrier1 * t);

sin1 = sin(2*pi*f_carrier1 * t);

x_upconv = real(txSig).* cos1 + imag(txSig) .* sin1;

%% === 接收端

x_training_wave = x_upconv;

x_training_msg = msg;

rxSig = [x_upconv(300:end) ; x_upconv];

% 1. 同步

x_resampled = resample(rxSig,1,1);

x_sync = sync_two_signals( x_resampled,x_training_wave,0);

figure(2);

plot(freq,20*log10(abs(fftshift(fft(x_sync))/max(abs(fftshift(fft(x_sync)))))));

ylim([-100,10])

xlim([0,freq(end)])

grid on;

xlabel('频率(Hz)');

title('接收信号');

% 2. 下变频 + 匹配滤波

xi_dnconv = x_sync .* cos1;

xq_dnconv = x_sync .* sin1;

x_filtered = xi_dnconv + 1j * xq_dnconv;

rxFilt = upfirdn(x_filtered, rrcFilter, 1, sps);

rxFilt = rxFilt(span+1:end-span); % 这是接收端匹配滤波后的信号

% 3. 均衡

% eq1 = lineareq(6, lms(0.01)); % LMS

eq1 = lineareq(30, rls(0.99,0.01)); % Create an equalizer object. % 40 taps，RLS算法，步长0.99，自相关矩阵逆矩阵的初值InvCorrInit对角线上的元素

eq1.SigConst = step(hMod,(0:M-1)')'; % Set signal constellation. % 标准星座图

[symbolest,~] = equalize(eq1,rxFilt,x_training_msg(1:trainlen)); % Equalize. % 均衡器obj，需要均衡的信号，训练序列

symbolest = symbolest ./ mean(abs(symbolest)) .* mean(abs(eq1.SigConst));

% Plot signals.

h = scatterplot(rxFilt,1,trainlen,'bx'); hold on;

scatterplot(symbolest,1,trainlen,'r.',h);

scatterplot(eq1.SigConst,1,0,'k*',h);

legend('Filtered signal','Equalized signal',...

'Ideal signal constellation');

hold off;

% Compute error rates with equalization.

hDemod = comm.RectangularQAMDemodulator(M);

demodmsg = step(hDemod,symbolest); % Demodulate detected signal from equalizer.

% Create ErrorRate Calculator System object

serVec = step(comm.ErrorRate,msg(trainlen+1:end),demodmsg(trainlen+1:end));

srate = serVec(1)

snum = serVec(2)

% Convert integers to bits

hIntToBit = comm.IntegerToBit(log2(M));

Tx_bit = step(hIntToBit, msg(trainlen+1:end));

Rx_bit = step(hIntToBit, demodmsg(trainlen+1:end));

% Calculate BER

berVec = step(comm.ErrorRate,Rx_bit,Tx_bit);

brate = berVec(1)

bnum = berVec(2)

同步的代码

function x_sync = sync_two_signals( x_resampled,x_training_wave,idx )

% sync_two_signals( x_resampled,x_training_wave,idx )

% x_resampled：收到的信号

% x_training_wave：用发送的信号

% idx：要找同步上的第几段。idx = 1,2,3,...

[hicorrI,lagsiI]=xcorr(x_resampled,x_training_wave);

[~,offsetindex]=max((hicorrI));

% offsetindex

for n = 2 : idx

% figure;plot(lagsiI,abs(hicorrI));

hicorrI(offsetindex) = -inf;

[~,offsetindex]=max(hicorrI);

end

% offsetindex

h=1;

x_sync=x_resampled(lagsiI(offsetindex)+h:lagsiI(offsetindex)+length(x_training_wave)+h-1);

end

function x_sync = sync_two_signals( x_resampled,x_training_wave,idx )

% sync_two_signals( x_resampled,x_training_wave,idx )

% x_resampled：收到的信号

% x_training_wave：用发送的信号

% idx：要找同步上的第几段。idx = 1,2,3,...

[hicorrI,lagsiI]=xcorr(x_resampled,x_training_wave);

[~,offsetindex]=max((hicorrI));

% offsetindex

for n = 2 : idx

% figure;plot(lagsiI,abs(hicorrI));

hicorrI(offsetindex) = -inf;

[~,offsetindex]=max(hicorrI);

end

% offsetindex

h=1;

x_sync=x_resampled(lagsiI(offsetindex)+h:lagsiI(offsetindex)+length(x_training_wave)+h-1);

end

误符号率

srate =  0.0041

错误符号数

snum =  37

误比特率

brate =  0.0021 错误比特数 bnum =  38