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+++ /dev/null
-function SNRvsBER_BPSKdiscrete(numBits)
- if nargin < 1
- numBits = 1000;
- end
-
- if isOctave()
- pkg load communications
- end
-
- %% SNR: Eb/N0
- snr_db = 0:0.2:10;
- snr = 10 .^ (snr_db ./ 10);
-
- %% Eb is assumed to be 1
- %% noise N ~ Gaussian(mean=0, variance=N0/2)
- N0 = 1 ./ snr;
-
- ber = zeros(1, length(snr));
-
- data = randomPSK(2, numBits);
-
- for i = 1:length(snr)
- noisyData = discreteAWGN(data, N0(i));
- decodedData = decodeNoisyBPSK(noisyData);
-
- bitErrors = sum(data ~= decodedData);
- ber(i) = bitErrors / numBits;
- end
-
- fig1 = figure(1);
- clf;
-
- %% Plot simulated results
- semilogy(snr_db, ber, 'r', 'LineWidth', 2);
- hold on;
-
- %% Plot theoretical curve
- %% BPSK: bit error when noise N > sqrt(Eb)
- %% Pr(N > sqrt(Eb))
- %% = Pr(Z > sqrt(Eb) / sqrt(N0/2))
- %% = Q(sqrt(2 * SNR))
- ber_th = qfunc(sqrt(2 * snr));
- semilogy(snr_db, ber_th, 'b', 'LineWidth', 1);
-
- grid on;
- xlabel('$E_b/N_0$ (dB)');
- ylabel('BER');
- legend('Simulated', '$Q\left(\sqrt{2 E_b / N_0}\right)$');
-
- formatFigure;
- saveas(gcf, strcat('BPSK_BER_SNR_', num2str(numBits), '.svg'));
-
-end
+++ /dev/null
-function x = decodeNoisyBPSK(noisyData)
- x = (noisyData > 0) - (noisyData <= 0);
-end
+++ /dev/null
-function x = discreteAWGN(data, N0)
- x = data + normrnd(0, sqrt(N0 / 2), 1, length(data));
-end
--- /dev/null
+function discretePSK_BER_SNR(M, numBits)
+ %% Set defaults for inputs
+ if nargin < 2
+ numBits = 1000;
+ end
+ if nargin < 1
+ M = 2;
+ end
+
+ if isOctave()
+ pkg load communications
+ end
+
+ EbN0_db = 0:0.2:10;
+ EbN0 = 10 .^ (EbN0_db ./ 10);
+
+ Es = 1;
+ Eb = Es / log2(M);
+ N0 = Eb ./ EbN0;
+
+ EsN0 = EbN0 .* log2(M);
+ EsN0_db = 10 .* log10(EsN0);
+
+ plotlen = length(EbN0);
+
+ ber = zeros(1, plotlen);
+
+ data = randi([0, M - 1], 1, numBits);
+ txsig = pskmod(data, M, 0, 'gray');
+
+ for i = 1:plotlen
+ rxsig = awgn(txsig, EsN0_db(i));
+ demodData = pskdemod(rxsig, M, 0, 'gray');
+
+ [bitErrors, ber(i)] = biterr(data, demodData);
+ end
+
+ fig1 = figure(1);
+ clf;
+
+ %% Plot simulated results
+ semilogy(EbN0_db, ber, 'r', 'LineWidth', 2);
+ hold on;
+
+ %% Plot theoretical curve
+ %% BPSK: bit error when noise Nr > sqrt(Eb)
+ %% Pr(Nr > sqrt(Eb))
+ %% = Pr(Z > sqrt(Eb) / sqrt(N0/2))
+ %%
+ %% QPSK = 2 BPSKs, one real and one imaginary, each with one bit
+ %% so BER is the same as BPSK (assuming Gray code)
+ if M == 2 || M == 4
+ ber_th = qfunc(sqrt(2 * EbN0));
+ semilogy(EbN0_db, ber_th, 'b', 'LineWidth', 1);
+ legend('Simulated', 'Theoretical');
+ else
+ %% Upper bound: R. Venkataramanan, Lent 2018, 3F4 Examples Paper 2
+ %% (Question 5), CUED.
+ %% Approximation: J.G. Proakis and M. Salehi, 2000, Contemporary
+ %% Communication Systems using MATLAB (Equations
+ %% 7.3.18 and 7.3.19), Brooks/Cole.
+ ber_ub = 2 * qfunc(sqrt(EbN0 * log2(M)) * sin(pi / M));
+ ber_ap = 2 * qfunc(sqrt(EbN0 * log2(M) * 2) * sin(pi / M)) / log2(M);
+ semilogy(EbN0_db, ber_ub, 'b', 'LineWidth', 1);
+ semilogy(EbN0_db, ber_ap, 'g', 'LineWidth', 1);
+ legend('Simulated', 'Upper bound', 'Approximation');
+ end
+
+ title(strcat(num2str(M), '-PSK with Gray code'));
+ grid on;
+ xlabel('$E_b/N_0$ (dB)');
+ ylabel('BER');
+
+ formatFigure;
+ saveas(gcf, strcat('BER_SNR_', num2str(M), 'PSK_', num2str(numBits), ...
+ '.svg'));
+end
+++ /dev/null
-function x = randomPSK(n, len)
- % symbols: nth roots of unity
- % i.e. solutions to polynomial x^n - 1 = 0
- symbols = roots([1 zeros(1, n-1) -1]);
-
- x = zeros(1, len);
- for i = 1:len
- x(i) = randomChoice(symbols);
- end
-end
-
-function x = randomChoice(arr)
- i = randi(length(arr));
- x = arr(i);
-end
projects / 4yp.git / commitdiff
