i have code for BPSK,QPSK and 16-QAM as given below and i want to code it for 8-psk, what are changes i have to make to below code for 8-psk .

*THE CODE IS *

function done = Space_Time_Coding_BER_Alamouti_split(nRx)

done=0; nTx = 2; % Number of Tx antennas filename = ['Alamouti_data_' num2str(nTx) 'x' num2str(nRx) ]; filevar = ['Eb_N0_dB'; 'maxEb '; 'Ber '; 'Ber4 '; 'Ber16 ']; BPSK = bin2dec(['0'; '1']); QPSK = bin2dec(['01'; '11'; '00'; '10']);

QAM16 = bin2dec(['1011'; '1001'; '0001'; '0011'; '1010'; '1000'; '0000'; '0010'; '1110'; '1100'; '0100'; '0110'; '1111'; '1101'; '0101'; '0111']); N=10^4; % Number of symbols to tx Eb_N0_dB = 0:30; % Multiple Eb/N0 values THRESHOLD = 100; % Minimum number of errors before proceeding to next SNR MAXITER=100; % Maximum number of iterrations before quiting

% Initialize some variables qam = 3; %The qam in use logM=0; % Bits per symbol k_QAM=0; % QAM factor for alphaRe=[]; % Real axis of constellation alphaIm=[]; % Real axis of constellation sqrtM = 0; % For calculating constellation k_qam = -1; % Unity transmit power scaling factor. BitErr=zeros(1,length(Eb_N0_dB)); % Array for counting biterrors SymbolErr=zeros(1,length(Eb_N0_dB)); % Array for counting biterrors maxEb = length(Eb_N0_dB); % Max SNR length indx =[]; % The index of the QAM constellation in increasing order modsetqam = []; % The current QAM constellation QAM_Matrix = []; % Matrix to help quickly calculate decision statistic blockTx = 2; % Number of transmissions per code block blockSym = 2; % Number of symbols sent per code block Rate = blockSym/blockTx; % The rate of the code block

% Convert N to even number of transmissions % For Alamouti, 2 transmissions per 2 symbols while(mod(N,blockSym)) N=N+1; end

for kk=1:3 %For each different QAM

    if(kk==1)
        qam = 2;
    elseif(kk==2)
        qam = 4;
    elseif(kk==3)
        qam = 16;
    end
    if(kk>1)
        % Calculate constellation
        QAMIQ = zeros(qam,1);
        sqrtM = sqrt(qam);
        logM = log2(qam); % bits per symbol
        xmin = -sqrtM + 1;
        xmax = sqrtM - 1;
        ymin = -sqrtM + 1;
        ymax = sqrtM - 1;
        alphaRe = xmin:2:xmax
        alphaIm = ymin:2:ymax;

        % Put the real and complex axis together
        ii=1;
        for y = alphaIm
            for x = alphaRe
                QAMIQ(ii)= x+y*1i;
                ii = ii+1;
            end
        end

        % For faster receiver due to Matlab
        QAM_Matrix = kron(QAMIQ,ones(1,N/nTx));

        % To normalize transmit power to unity
        % Average power for 16 qam is sqrt(10)

        if(qam==16)
            k_QAM = 1/sqrt(10);
            [tt indx] = sort(QAM16);
            mod_set = QAM16;
        elseif(qam==4)
            k_QAM = 1;
            [tt indx] = sort(QPSK);
            mod_set = QPSK;
        end
    else
        logM = log2(qam); % bits per symbol
        k_QAM = 1;
        [tt indx] = sort(BPSK);
        mod_set = BPSK;
        QAMIQ = [-1; 1];
        QAM_Matrix = kron(QAMIQ,ones(1,N/nTx));
    end

    % Begin simulation
    for ii = 1:length(Eb_N0_dB)
        countiter = 0; % Number of iterations
        fprintf('\n At SNR = %d of %s \n',Eb_N0_dB(ii),strtrim(filevar(kk+2,:)));
        while(THRESHOLD>BitErr(ii) && countiter<MAXITER)
            countiter = countiter+1;
            % TRANSMITTER SIDE
            NNew=N*nTx/Rate; % New size of transmitted signal;
            s = zeros(1,NNew); % space-time coded modulated transmitted sequence

            % generate random signal
            transmitted = randintt(N,1,[0,qam-1]); % transmitted sequence in decimal
            % modulate random signal
            bitmod = QAMIQ(indx(transmitted+1)) ;
            % normalize transmit power to one
            s_precoded = bitmod *k_QAM; % uncoded modulated transmitted sequence

            % Perform Space-Time Coding
            d_btwc = blockTx*nTx; % Distance between blocks
            s(1:d_btwc:NNew)=s_precoded(1:blockSym:N); % s1
            s(2:d_btwc:NNew)=s_precoded(2:blockSym:N); % s2
            s(3:d_btwc:NNew)= -(conj(s_precoded(2:blockSym:N))); % -s2*
            s(4:d_btwc:NNew)= conj(s_precoded(1:blockSym:N)); % s1*

            %CHANNEL
            % Expand for easy multiplication with channel matrix h
            % (much faster than using matlab's matrix multiplication)
            sMod = kron(s,ones(nRx,1));
            % Add a third dimension for easy product multiplication
            sMod = reshape(sMod,[nRx,nTx,NNew/nTx]);

            % Rayleigh channel, generate one every two transmissions
            h_orig = 1/sqrt(2)*(randn(nRx,nTx,N/nTx) + 1i*randn(nRx,nTx,N/nTx));

            % Repeat the channel every two transmissions:
            dummyarray=ones(blockTx,1);
            hprime = reshape(h_orig,nRx*nTx,[]);
            h=reshape(kron(dummyarray,hprime),nRx,nTx,[]);

            % white gaussian noise, 0dB variance
            n = 1/sqrt(2)*(randn(nRx,NNew/nTx) + 1i*randn(nRx,NNew/nTx));

            % Channel and noise Noise addition
            % Here we keep the signal power the same and add variance
            % to the noise, which is equivalent to decreasing the signal
            % and having a 0dB variance noise at the RX, then amplifying
            % the signal, and therefore amplifying the noise (more
            % variance).
            SNR = 10^(Eb_N0_dB(ii)/10); % SNR in linear scale
            variance = nTx/(2*SNR); % Variance
            sigma = sqrt(variance); % Standard Deviation
            y = reshape(sum(h.*sMod,2),nRx,[]) + sigma*n; % received signal
            % sMod = [s1 s2 s3 s4 ... ; s1 s2 s3 s4 ...];
            % sum(h.*sMod,2) multiplies each element of h with sMod and
            % adds each row

            % RECEIVER SIDE
            % Amplify for detection
            y= y./k_QAM;
            % Maximum-likelihood detection
            h_orig = reshape(h_orig,nRx,[]);

            % Decision Statistic for s1
            % r1^j = y(:,1:2:end)
            % r2^j = y(:,2:2:end)
            % alpha1,j = h_orig(:,1:2:end)
            % alpha2,j = h_orig(:,2:2:end)
            firstterm = sum(y(:,1:blockTx:end).*conj(h_orig(:,1:nTx:end))...
                +conj(y(:,2:nTx:end)).*h_orig(:,2:nTx:end),1);
            secondtermTemp = sum(abs(h_orig).^2,1);
            secondterm = secondtermTemp(1:nTx:end);
            for TxAnt = 2:nTx
                secondterm = secondterm + secondtermTemp(TxAnt:nTx:end);
            end
            secondterm = -1 + secondterm;

            % For ease of computing due to Matlab
            firstterm_Matrix = kron(firstterm,ones(qam,1));
            secondterm_Matrix = kron(secondterm,ones(qam,1));

            %Now check for every possible s1, and get min
            s1_decision = abs((firstterm_Matrix - QAM_Matrix)).^2 ...
                        + secondterm_Matrix.*abs(QAM_Matrix).^2;

            [s1_min s1_index] = min(s1_decision);

            received_s1 = mod_set(s1_index);

            % Decision Statistic for s2
            % r1^j = y(:,1:2:end)
            % r2^j = y(:,2:2:end)
            % alpha1,j = h_orig(:,1:2:end)
            % alpha2,j = h_orig(:,2:2:end)
            firstterm = sum(y(:,1:blockTx:end).*conj(h_orig(:,2:blockTx:end))...
                -conj(y(:,2:blockTx:end)).*h_orig(:,1:blockTx:end),1);

            % For ease of computing due to Matlab
            firstterm_Matrix = kron(firstterm,ones(qam,1));

            %Now check for every possible s1, and get min
            s2_decision = abs((firstterm_Matrix - QAM_Matrix)).^2 ...
                        + secondterm_Matrix.*abs(QAM_Matrix).^2;

            [s2_min s2_index] = min(s2_decision);

            received_s2 = mod_set(s2_index);

            received = zeros(N,1);
            received(1:blockSym:end)=received_s1;
            received(2:blockSym:end)=received_s2;

            errors = biterrr(received,transmitted);

            if(errors)
                fprintf('x');
            else
                fprintf('.');
            end
            BitErr(ii) = BitErr(ii) + errors;
        end
        if(BitErr(ii)==0)
            maxEb = ii;
            break;
        end
        BitErr(ii) = BitErr(ii)./(N*logM*countiter);
    end
    if(kk==1)
        Ber = BitErr;
        tempname = [filename '-' strtrim(filevar(kk+2,:)) '.mat'];
        save(tempname, strtrim(filevar(1,:)), ...
            strtrim(filevar(2,:)), strtrim(filevar(kk+2,:)));
    elseif(kk==2)
        Ber4 = BitErr;
        tempname = [filename '-' strtrim(filevar(kk+2,:)) '.mat'];
        save(tempname, strtrim(filevar(1,:)), ...
            strtrim(filevar(2,:)), strtrim(filevar(kk+2,:)));
    else
        Ber16 = BitErr;
        tempname = [filename '-' strtrim(filevar(kk+2,:)) '.mat'];
        save(tempname, strtrim(filevar(1,:)), ...
            strtrim(filevar(2,:)), strtrim(filevar(kk+2,:)));

    end
    BitErr=zeros(1,length(Eb_N0_dB)); 
end
fprintf('\n');
done = 1;

PLEASE HELP ME TO SOLVE THIS,

Answer 1

[Eda Pejtamalli]

I can get error when I try to run it: Error: File: Untitled.m Line: 173 Column: 5 Illegal use of reserved keyword "end".

I can't fix it, any suggestions?