Hi guys, I have a for loop, but every iteration overwrites the variable(max_run), and I have only the final data left.. How can I save data from every loop? I saw some other questions like my issue, but I always get an error"Improper assignment with

%% BPSK Generation clear all; close all; clc; N = 2*10^4; % number of bits or symbols ip = rand(1,N)>0.5; % generating 0,1 with equal probability s = 2*ip-1; % BPSK modulation 0 -> -1; 1 -> 1

%% Prepare transmitted signal

m=2; % oversampling factor beta=0.3; % rolloff parameter for SRRC l=100; % 1/2 length of pulse shape (in symbols) chan=[1]; % T/m "channel" toffset=-0.5; % initial timing offset pulshap=srrc(l,beta,m,toffset); % SRRC pulse shape sup=zeros(1,N*m); % upsample the data by placing... sup(1:m:end)=s; % ... p zeros between each data point hh=conv(pulshap,sup); % ... and pulse shape r1=conv(hh,chan); % ... to get received signal

%% Noise Generation

SNRdB=1:2:13; % Signal to Noise Ratio SNR=10.^(SNRdB/10);

for cv=1:length(SNR);

no=sqrt((1/SNR(cv)))*randn(1,40400); % Noise generation r=r1+no; % Adding the noise to the received signal

    %%Matched Filter & Convolution process

    matchfilt=srrc(l,beta,m,0);          % filter = pulse shape
    x=conv(r,matchfilt);                 % convolve signal with matched filter

    %%Run clock recovery algorithm

    tnow=2*l*m+1; tau=0; xs=zeros(1,N);         % initialize variables
    tausave=zeros(1,N); tausave(1)=tau; i=0;
    mu=0.05;                                    % algorithm stepsize
    delta=0.1;                                  % time for derivative

    while tnow<length(x)-2*l*m                  % run iteration
      i=i+1;
      xs(i)=interpsinc(x,tnow+tau,l);           % interpolated value at tnow+tau
      x_deltap=interpsinc(x,tnow+tau+delta,l);  % get value to the right
      x_deltam=interpsinc(x,tnow+tau-delta,l);  % get value to the left
      dx=x_deltap-x_deltam;                     % calculate numerical derivative  
      tau=tau+mu*dx*xs(i);                      % alg update (energy)
      tnow=tnow+m; tausave(i)=tau;              % save for plotting
      indexmin = find(tausave >= 0.5);          % finding iteration value.. 
      max_run = min(indexmin)                        % automaticlly 
    end

    % Plot results
    figure, subplot(2,1,1),  plot(xs(1:i-2),'b.'); 
    legend([ 'SNR=' int2str(SNR(cv))]);        % plot constellation diagram
    title('constellation diagram');
    ylabel('estimated symbol values')
    subplot(2,1,2), plot(tausave(1:i-2)) 
    ylabel('offset estimates'), xlabel('iterations')
    legend([ 'SNR=' int2str(SNR(cv))]);

end

Answer 1

[Alexandra Harkai]

One way of doing it would be to maintain an array of max_run(i) values.

max_run(i) = min(indexmin)

Instead of

max_run = min(indexmin)

Of course it is then a good idea to initialise max_run before the loop to be an all zeros array to allocate sufficient memory.