关于“Matlab Demos”的学习和总结_matlab学习总结总结
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关于“Matlab Demos”的学习和总结
这里总结了Matlab Demos下通信工具箱里面的examples，给出源代码和注释。
程序代码(一):关于BPSK的Mente Carlo仿真
%-----------% Matlab Demos
No.1.1 %-----------% Phase Shift Keying Simulation % This demo shows how to simulate a basic Quarternary Phase Shift Keying %(QPSK)communication link, and to generate empirical performance curves % that can be compared to theoretical predictions.%-----------% 1.两个函数的使用：rectpulse与intdump成对使用，重复插值与抽取，互为逆操作； % 2.randn的seed的使用；
% 3.这里的解调是直接采用MATLAB自带的pskmod、pskdemod函数；
% 4.为什么在后面调用函数，当采用的EbNo越大的时候，计算需要的时间越长？甚至是
%
系统死机（大概超过10dB之后）？
% 5.这里需要讨论的问题就是 Mente Carlo 仿真的数值问题，即当用一个试验样本函数去
%
估计一个观测值的时候，如何尽量减小估计值的方差问题（选择合适的仿真点总数和期望错误点数）。%-----------%
revised by lavabin 2006.07.26 %-----------clc;clear all;close all;echo off;tic;%-----------%
Parameter Definition %-----------nSamp = 8;numSymb = 100;
M = 4;SNR = 14;
seed = [12345 54321];
rand('state', seed(1));randn('state', seed(2));%-----------%
Generating random information symbols %-----------numPlot = 10;rand('state', seed(1));msg_orig = randsrc(numSymb, 1, 0:M-1);%-----------% Phase modulating the data
% Use PSKMOD to phase modulate the data and RECTPULSE to upsample to a % sampling rate 8 times the carrier frequency.%-----------grayencod = bitxor(0:M-1, floor((0:M-1)/2));
% Gray coding here!% % a = bitxor(0:M-1, floor((0:M-1)/2))% % a = 0msg_gr_orig = grayencod(msg_orig+1);% % Using “looktable” to map source data to Gray code msg_tx = pskmod(msg_gr_orig,M);% % Mapping source data to MPSK constellation msg_tx = rectpulse(msg_tx,nSamp);%-----------------------------% figure(1);%-----------------------------scatterplot(msg_tx);hold on;grid on;%-----------% Creating the noisy signal % Then use AWGN to add noise to the transmitted signal to create the noisy % signal at the receiver.Use the 'measured' option to add noise that is % 14 dB below the average signal power(SNR = 14 dB).Plot the % constellation of the received signal.%-----------randn('state', seed(2));msg_rx = awgn(msg_tx, SNR, 'measured', [], 'dB');%-----------------------------% figure(2);
%-----------------------------scatterplot(msg_rx);hold on;grid on;%-----------% Recovering information from the transmitted signal % Use INTDUMP to downsample to the original information rate.Then use % PSKDEMOD to demodulate the signal, and detect the transmitted symbols.% The detected symbols are plotted in red stems with circles and the % transmitted symbols are plotted in blue stems with x's.The blue stems of % the transmitted signal are shadowed by the red stems of the received % signal.Therefore, comparing the blue x's with the red circles indicates % that the received signal is identical to the transmitted signal.%-----------msg_rx_down = intdump(msg_rx,nSamp);% operation before DEMOD msg_gr_demod = pskdemod(msg_rx_down,M);[dummy graydecod] = sort(grayencod);graydecod = graydecod(11;% Drive the simulation for each of the SNR values calculated above for idx2 = 1:length(EsNo)
% Exit loop only when minimum number of iterations have completed and the
% number of errors exceeds 'expSymErrs'
idx = 1;
while((idx logical or %
while(idx
% Generate random numbers from in the range [0, M-1]
msg_orig = randsrc(symbPerIter, 1, 0:M-1);
% Gray encode symbols
msg_gr_orig = grayencod(msg_orig+1)';
% Digitally modulate the signal
msg_tx = pskmod(msg_gr_orig, M);
% Add Gauian noise to the signal.The noise is calibrated using
% the 'measured' option.msg_rx = awgn(msg_tx, EsNo(idx2), 'measured', [], 'dB');
% Demodulate the signal
msg_gr_demod = pskdemod(msg_rx, M);
% Gray decode meage
msg_demod = graydecod(msg_gr_demod+1)';
% Calculate bit error count, BER, symbol error count and SER,% for this iteration.[errBit(idx)ratBit(idx)] = biterr(msg_orig, msg_demod, k);
[errSym(idx)ratSym(idx)] = symerr(msg_orig, msg_demod);
% Increment for next iteration
idx = idx + 1;
end
% average the errors and error ratios for the iterations.errors(idx2, :)= [sum(errBit), sum(errSym)];
ratio(idx2, :)= [mean(ratBit), mean(ratSym)];% %
函数说明 mean：
% %
MEAN
Average or mean value.% %
For vectors, MEAN(X)is the mean value of the elements in X.For % %
matrices, MEAN(X)is a row vector containing the mean value of % %
each column.% Plot the simulated results for SER and BER.semilogy(EbNo(1:size(ratio(:,2),1)), ratio(:,2), 'bo',...EbNo(1:size(ratio(:,1),1)), ratio(:,1), 'ro');
legend('Theoretical SER','Theoretical BER','Simulated SER','Simulated BER',0);
drawnow;end hold off;%-----------%
End of Function %-----------% % 函数说明：
% % DRAWNOW Flush pending graphics events.% %
DRAWNOW “flushes the event queue” and forces MATLAB to % %
update the screen.% %
% %
There are four events that cause MATLAB to flush the event % %
queue and draw the screen: % %
% %
-a return to the MATLAB prompt % %
-hitting a PAUSE statement % %
-executing a GETFRAME command % %
-executing a DRAWNOW command
程序代码(二): 程序代码(三): 关于升余弦滤波器
%-----------% Matlab Demos
No.3.1 %-----------% Raised Cosine Filtering %-----------%(1)% This demonstration uses the Communications Toolbox functions, RCOSINE and % RCOSFLT, to demonstrate the ISI rejection capability of the raised cosine % filter.%(2)% It demonstrates how to use RCOSINE and RCOSFLT, how the raised cosine
% filter controls intersymbol interference, and how to split % the raised cosine filtering between transmitter and receiver.%(3)% This data sequence represents a digital sequence that will be upsampled by % zero-padding before filtering.Raised cosine filters will be used to shape % the waveform without introducing intersymbol interference(ISI).%-----------% 几点主要的意思：
% 1
“升余弦函数 rcosine” 和 “升余弦滤波器函数 rcosflt”的使用；
% 2
波形成形的目标是在源端就利用升余弦函数的抗ISI特性消除ISI，因为不可能生成 %
绝对的的时域有限的信号； % 3
升余弦滤波器在源/宿端的分割。% % 从上到下几个code板块依次讨论了: % % Delay的影响 % % R的影响
% % 发、收端之间平方根升余弦滤波 % % 缺省方式下的rcosflt的快速调用方法
%-----------%
revised by lavabin 2006.08.02 %-----------clc;clear all;close all;echo off;tic;%-----------%
Parameter Definition %-----------Delay = 3;DataL = 20;R =.5;Fd = 1;Fs = 8;PropD = 0;% Generate random data.x = randsrc(DataL, 1, [], 1245);% at time 0, 1/Fd, 2/Fd,...% Fd is the sampling frequency of the data source % 1/Fd is the symbol period of the data source tx = [PropD: PropD + DataL1]./ Fd;% figure(2)% figure1 与 figure2的波形对比强烈地反映出了Delay的作用，滤波器输出的波形与输入
% 波形在包络上的相似性需要通过延迟输入信号来得到保证 figure;stem(tx, x, 'kx');hold on;plot(to, yo, 'b.');hold off;axis([0 30-1.6 1.6]);xlabel('Time');ylabel('Amplitude');%-----------% This step demonstrates the effect that changing the rolloff factor from.5 %(blue curve)to.2(red curve)has on the resulting filtered output.The % lower value for rolloff causes the filter to have a narrower transition band % causing the filtered signal overshoot to be greater for the red curve than for % the blue curve.%----------% Design filter.[yg, tg] = rcosine(Fd, Fs, 'fir',.2, Delay);% Filter data.[yo1, to1] = rcosflt(x, Fd, Fs, 'normal/fir/filter',yg);% figure(3)figure;stem(tx, x, 'kx');hold on;% Plot filtered data.plot(to, yo, 'b-',to1, yo1, 'r-');hold off;% Set axes and labels.axis([0 30-1.6 1.6]);xlabel('Time');ylabel('Amplitude');legend('Source Data','R = 0.5','R = 0.2')%-----------% A typical use of raised cosine filtering is to split the filtering between % transmitter and receiver.The data stream is upsampled and filtered at the % transmitter using the square-root raised cosine filter.This plot shows % the transmitted signal when filtered using the square-root raised cosine % filter.The “fir/sqrt” switch was used with RCOSINE to generate the % square-root raised cosine filter.%-----------% Design square root filter.[ys, ts] = rcosine(Fd, Fs, 'fir/sqrt', R, Delay);% Filter at the transmitter.[yc, tc] = rcosflt(x, Fd, Fs, 'filter', ys);% figure(4)figure;stem(tx, x, 'kx');hold on;plot(tc, yc, 'm.');hold off;axis([0 30-1.6 1.6]);xlabel('Time');ylabel('Amplitude');%-----------% The transmitted signal(magenta curve)is then filtered, but not upsampled, at % the receiver, using the same square-root raised cosine filter, resulting in a % signal depicted by the blue curve at the receiver.The resulting signal is % virtually identical to the signal filtered using a single raised cosine % filter.The “Fs” was used to filter without upsampling.%-----------% Filter at the receiver.[yr, tr] = rcosflt(yc, Fd, Fs, 'filter/Fs', ys);% Adjust for propagation delay.tcc = tc + Delay.* Fd;txx = tx + Delay.* Fd;% figure(5)figure;stem(txx, x, 'kx');hold on;plot(tcc, yc, 'm-',tr, yr, 'b-');hold off;axis([0 30-1.6 1.6]);xlabel('Time');ylabel('Amplitude');%-----------% This step demonstrates a quicker way to filter data using RCOSFLT.When % RCOSFLT is used without the “filter” type switch, it designs a filter and uses % it to filter the input data.This step creates the same plot as before but % designs the raised cosine filter and generates the filtered stream in one % command.%-----------% Design and filter.[yo2, to2] = rcosflt(x, Fd, Fs, 'normal/fir', R, Delay);% figure(6)figure;stem(tx, x, 'kx');hold on;plot(to2, yo2, 'b-');hold off;axis([0 30-1.6 1.6]);xlabel('Time');ylabel('Amplitude');%-----------displayEndOfDemoMeage(mfilename)%-----------simulation_time = toc %-----------%
End of Script %-----------% % 关于rcosflt的函数说明
%-----------% % RCOSFLT Filter the input signal using a raised cosine filter.% %
Y = RCOSFLT(X, Fd, Fs, TYPE_FLAG, R, DELAY)filters the input signal X % %
using a raised cosine FIR filter.The sample frequency for the input, X, % %
is Fd(Hz).The sample frequency for the output, Y, is Fs(Hz).Fs must be % %
an integer multiple of Fd.The TYPE_FLAG gives specific filter design % %
or filtering options.The rolloff factor, R, determines the width of the % %
transition band of the filter.DELAY is the time delay from the beginning % %
of the filter to the peak of the impulse response.% %
% %
R, the rolloff factor specifies the exce bandwidth of the filter.R must % %
be in the range [0, 1].For example, R =.5 means that the bandwidth of the % %
filter is 1.5 times the input sampling frequency, Fd.This also means that % %
the transition band of the filter extends from.5 * Fd and 1.5 * Fd.Since % %
R is normalized to the input sampling frequency, Fd, it has no units.% %
Typical values for R are between 0.2 to 0.5.% %
% %
DELAY determines the group delay of the filter.The group delay is the % %
opposite of the change in filter phase with respect to frequency.For linear % %
phase filters, the group delay is also the time delay between the input % %
signal and the peak response of the filter.DELAY also determines the % %
length of the filter impulse response used to filter X.This delay is % %
Fs/Fd *(2 * DELAY + 1).% %
% %
Y is the output of the upsampled, filtered input stream X.The length of % %
vector Y is % %
Fs/Fd *(length(X)+ 2 * DELAY).% %
% %
TYPE_FLAG is a string which may contain any of the option strings listed % %
below delimited by a '/' For example, the 'iir' and 'Fs' flags may % %
be combined as 'iir/Fs'.While some of the pairs of option substrings % %
are mutually exclusive, they are not mutually exclusive in general.% % % %
'fir'
Design an FIR filter and use it to filter X.When the 'filter' % %
TYPE_FLAG is not used, an FIR filter is designed and used to % %
filter X.See the 'filter' TYPE_FLAG description for the behavior % %
when the 'fir' and 'filter' TYPE_FLAGs are used together.This % %
option is exclusive of the 'iir' substring.% %
% %
'iir'
Design an IIR filter and use it to filter X.When the 'filter' % %
TYPE_FLAG is not used, an IIR approximation to the equivalent FIR % %
filter is designed and used to filter X.See the 'filter' % %
TYPE_FLAG description for the behavior when the 'iir' and 'filter' % %
TYPE_FLAGs are used together.This option is exclusive of the % %
'fir' substring.% % % %
'normal' Design a normal raised cosine filter and use it to filter X.The % %
filter coefficients are normalized so the peak coefficient is one.% %
This option is exclusive of the 'sqrt' substring.% %
% %
'sqrt'
Design a square root raised cosine filter and use it to filter X.% %
The filter coefficients are normalized so that the impulse % %
response of this filter when convolved with itself will result % %
in an impulse response that is approximately equal to the 'normal' % %
raised cosine filter.The difference in this approximation is due % %
to finite filter length.This is a useful option when the raised % %
cosine filtering is split between transmitter and receiver by % %
using the 'sqrt' filter in each device.This option is exclusive % %
of the 'normal' substring.% %
% %
'Fs'
X is input with sample frequency Fs(i.e., the input signal has % %
Fs/Fd samples per symbol).In this case the input signal is not % %
upsampled from Fd to Fs but is simply filtered by the raised % %
cosine filter.This is useful for filtering an oversampled data % %
stream at the receiver.When using the 'Fs' substring, the length % %
of vector, Y is % %
length(X)+ Fs/Fd * 2 * DELAY.% %
% %
'filter' Means the filter is provided by the user.When using the 'filter' % %
TYPE_FLAG, the input parameters are: % %
% %
Y = RCOSFLT(X, Fd, Fs, TYPE_FLAG, NUM)filters with % %
a user-supplied IIR filter.When TYPE_FLAG contains both 'filter' % %
and 'iir' type substrings, the IIR filter defined by numerator, % %
NUM, and denominator, DEN, is used as to filter X.The DELAY % %
parameter is used to force RCOSFLT to behave as if the filter were % %
designed by RCOSFLT using the same DELAY parameter.The DELAY % %
parameter should match the DELAY parameter used to design the % %
filter defined by NUM and DEN in the RCOSINE function.The default % %
value of DELAY is 3.% %
% %
The raised cosine filter should be designed using the RCOSINE % %
function.% %
% %
Y = RCOSFLT(X, Fd, Fs, TYPE_FLAG, R)filters the input signal X % %
using a raised cosine filter and default DELAY parameter, 3.% %
% %
Y = RCOSFLT(X, Fd, Fs, TYPE_FLAG)filters the input signal X using a % %
raised cosine filter and the following default parameters % %
DELAY = 3 % %
R =.5 % %
% %
Y = RCOSFLT(X, Fd, Fs)filters the input signal X using a raised cosine % %
filter and the following default parameters % %
DELAY = 3 % %
R =.5 % %
TYPE_FLAG = 'fir/normal' % %
% %
Y = RCOSFLT(X, Fd, Fs, TYPE_FLAG, R, DELAY, TOL)specifies the % %
tolerance in IIR filter design.The default value for TOL is.01.% %
% %
[Y, T] = RCOSFLT(...)returns the time vector in T.%-----------
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