To plot Bit Error Rate (BER) versus receiver sensitivity for different modulation schemes in MATLAB:
1. Choose the modulation schemes to compare, such as BPSK, QPSK, and 16-QAM.
2. Set up an SNR (Signal-to-Noise Ratio) range in dB for the analysis.
3. Map each SNR value to a receiver sensitivity value. For illustration, you can assume that 0 dB SNR corresponds to -80 dBm sensitivity, and shift the SNR range accordingly.
4. Use standard BER formulas for each modulation:
a) BPSK/QPSK: BER = 0.5 * erfc(sqrt(SNR))
b) 16-QAM (approximate): BER = (3/8) * erfc(sqrt(SNR/10))
5. Calculate BER values for each modulation scheme across the sensitivity range.
6. Plot BER versus receiver sensitivity on a semilogarithmic scale to compare the performance of each modulation format.
Below is an example MATLAB script that implements this process:
% Define SNR range (in dB)
SNR_dB = -10:1:20;
SNR = 10.^(SNR_dB/10); % Convert SNR from dB to linear scale
% Map SNR to receiver sensitivity (illustrative)
% Assume -80 dBm sensitivity at 0 dB SNR
sensitivity = SNR_dB - 80;
% Compute BER for each modulation scheme
BER_BPSK = 0.5 * erfc(sqrt(SNR)); % BPSK
BER_QPSK = BER_BPSK; % QPSK (same as BPSK)
BER_16QAM = (3/8) * erfc(sqrt(SNR/10)); % 16-QAM (approximate)
% Plot results
figure;
semilogy(sensitivity, BER_BPSK, 'b-o', 'LineWidth', 2); hold on;
semilogy(sensitivity, BER_QPSK, 'r-s', 'LineWidth', 2);
semilogy(sensitivity, BER_16QAM, 'g-^', 'LineWidth', 2);
xlabel('Receiver Sensitivity (dBm)');
ylabel('Bit Error Rate (BER)');
title('BER vs. Receiver Sensitivity for Different Modulation Schemes');
legend('BPSK', 'QPSK', '16-QAM');
grid on;
More modulation schemes can be added as needed by including their BER formulas.
To know more about the “erfc()” and “semilogy()” function, run the following commands respectively:
doc erfc
doc semilogy
Hope this is helpful!
