Skip to main content
Login Wireless Communication Modulation MATLAB Beamforming Project Ideas MIMO Computer Networks

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...


 

MATLAB Script for BER vs. SNR for M-QAM, M-PSK, QPSk, BPSK


Output





If M>8, the distance between constellation points is short, and a higher Eb/No (SNR per Bit) ratio is required to reach the desired BER. Although the mapping from the data bits is arbitrary, some data bits are typically used. Every constellation point in the M-PSK constellation has two neighbors, each with an equal chance of making an error. As there are four bits per symbol, BER assumes a one-bit error for every mistake in a character. The demodulator in PSK must be able to calculate the received sinusoid's phase about some reference phase. While using the same bandwidths as ASK, PSK is less prone to errors than ASK. Also, using bandwidth with a significant data rate is more effective.

In the above figure, it is clear that PSK is more robust than QAM in the context of noise resilience. QAM modulations, including 16-QAM, are sensitive to both amplitude and phase errors. As you increase the number of constellation points (e.g., from 16-QAM to 8-PSK), the signal becomes more susceptible to amplitude and phase noise. In contrast, PSK modulations primarily rely on phase information and may be less sensitive to amplitude variations. This can make 8-PSK more robust in this scenario. 

QAM schemes require a higher SNR to achieve the same error rates as PSK schemes with the same number of constellation points. This means that 16-QAM may require a higher SNR than 8-PSK to achieve a satisfactory bit error rate (BER) or symbol error rate (SER). In practical communication systems, achieving the necessary SNR can be challenging, especially in noisy or fading channels.

MATLAB Code for BER vs SNR for m-ary QAM

clc;
clear all;
close all;


% Set parameters
snr_dB = -20:2:20; % SNR values in dB
qam_orders = [4, 16, 64, 256]; % QAM modulation orders

% Loop through each QAM order
for qam_order = qam_orders
% Calculate theoretical BER using berawgn
ber = berawgn(snr_dB, 'qam', qam_order);

% Plot the results
semilogy(snr_dB, ber, 'o-', 'DisplayName', sprintf('%d-QAM', qam_order));
hold on;
end

% Add labels and legend
title('BER vs SNR for Variable QAM');
xlabel('SNR (dB)');
ylabel('Bit Error Rate (BER)');
grid on;
legend('Location', 'best');

Output

 

Fig: BER vs SNR graph for Various QAM
 

Copy the aforementioned MATLAB Code for BER vs SNR for   m-ary QAM from Here

 

 

MATLAB Code for BER vs SNR for m-ary PSK

clc;
clear all;
close all;

% Parameters
num_symbols = 1e5; % Number of symbols
snr_db = 0:2:20; % Range of SNR values in dB

% PSK orders to be tested
psk_orders = [2, 4, 8, 16, 32];

% Initialize BER arrays
ber_results = zeros(length(psk_orders), length(snr_db));

% BER calculation for each PSK order and SNR value
for i = 1:length(psk_orders)
psk_order = psk_orders(i);

for j = 1:length(snr_db)
% Generate random symbols
data_symbols = randi([0, psk_order-1], 1, num_symbols);

% Modulate symbols to generate signal
modulated_signal = pskmod(data_symbols, psk_order);

% Add AWGN to the signal
snr_linear = 10^(snr_db(j)/10);
received_signal = awgn(modulated_signal, snr_db(j), 'measured');

% Demodulate received signal
demodulated_symbols = pskdemod(received_signal, psk_order);

% Calculate BER
ber_results(i, j) = sum(data_symbols ~= demodulated_symbols) / num_symbols;
end
end

% Plot BER vs. SNR
figure;
semilogy(snr_db, ber_results(1, :), 'o-', 'DisplayName', 'BPSK');
hold on;

for i = 2:length(psk_orders)
semilogy(snr_db, ber_results(i, :), 'o-', 'DisplayName', sprintf('%d-PSK', psk_orders(i)));
end

title('BER vs. SNR for Various PSK Schemes');
xlabel('SNR (dB)');
ylabel('Bit Error Rate (BER)');
legend('Location', 'best');
grid on;
hold off;

Output

 
 
Fig: BER vs SNR graph for various PSK
 

Copy the above code for BER vs SNR for m-ary PSK from here



Read more about
[1] BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, and others

People are good at skipping over material they already know!

View Related Topics to







Admin & Author: Salim

profile

  Website: www.salimwireless.com
  Interests: Signal Processing, Telecommunication, 5G Technology, Present & Future Wireless Technologies, Digital Signal Processing, Computer Networks, Millimeter Wave Band Channel, Web Development
  Seeking an opportunity in the Teaching or Electronics & Telecommunication domains.
  Possess M.Tech in Electronic Communication Systems.


Contact Us

Name

Email *

Message *

Popular Posts

MATLAB code for MSK

๐Ÿ“˜ Overview ๐Ÿงฎ MATLAB Codes ๐Ÿงฎ Theory ๐Ÿงฎ Simulator for MSK ๐Ÿ“š Further Reading  Copy the MATLAB Code from here % The code is developed by SalimWireless.com clc; clear; close all; % Define a bit sequence bitSeq = [0, 1, 0, 0, 1, 1, 1, 0, 0, 1]; % Perform MSK modulation [modSignal, timeVec] = modulateMSK(bitSeq, 10, 10, 10000); % Plot the modulated signal subplot(2,1,1); samples = 1:numel(bitSeq); stem(samples, bitSeq); title('Original message signal'); xlabel('Time (s)'); ylabel('Amplitude'); % Plot the modulated signal subplot(2,1,2); samples = 1:10000; plot(samples / 10000, modSignal(1:10000)); title('MSK modulated signal'); xlabel('Time (s)'); ylabel('Amplitude'); % Perform MSK demodulation demodBits = demodMSK(modSignal, 10, 10, 10000); % Function to perform MSK modulation function [signal, timeVec] = modulateMSK(bits, carrierFreq, baudRate, sampleFreq) % Converts a binary bit sequence in...
Read more

Comparisons among ASK, PSK, and FSK | And the definitions of each

๐Ÿ“˜ Overview ๐Ÿงฎ Simulator ๐Ÿงฎ Noise Sensitivity, Bandwidth, Complexity, etc. ๐Ÿงฎ MATLAB Codes ๐Ÿงฎ Some Questions and Answers ๐Ÿ“š Further Reading Modulation ASK, FSK & PSK Constellation MATLAB Simulink MATLAB Code Comparisons among ASK, PSK, and FSK    Comparisons among ASK, PSK, and FSK   Simulator for Calculating Bandwidth of ASK, FSK, and PSK The baud rate represents the number of symbols transmitted per second. Both baud rate and bit rate are same for binary ASK, FSK, and PSK. Select Modulation Type: ASK FSK PSK Baud Rate or Bit Rate (bps): Frequency Deviation (Hz) for FSK: Calculate Bandwidth Comparison among ASK,  FSK, and PSK Performance Comparison: 1. Noise Sensitivity:    - ASK is the most sensitive to noise due to its r...
Read more

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

๐Ÿ“˜ Overview of BER and SNR ๐Ÿงฎ Simulator for m-ary QAM and m-ary PSK ๐Ÿงฎ MATLAB Codes ๐Ÿ“š Further Reading Modulation Constellation Diagrams BER vs. SNR BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ... What is Bit Error Rate (BER)? The abbreviation BER stands for bit error rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. It is defined as,  In mathematics, BER = (number of bits received in error / total number of transmitted bits)  On the other hand, SNR refers to the signal-to-noise power ratio. For ease of calculation, we commonly convert it to dB or decibels.   What is Signal the signal-to-noise ratio (SNR)? SNR = signal power/noise power (SNR is a ratio of signal power to noise power) SNR (in dB) = 10*log(signal power / noise power) [base 10] For instance,...
Read more

MATLAB Code for BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc

๐Ÿ“˜ Overview ๐Ÿงฎ MATLAB Codes ๐Ÿงฎ Theory ๐Ÿงฎ Are QPSK and 4-PSK same? ๐Ÿ“š Further Reading   QPSK offers double the data rate of BPSK while maintaining a similar bit error rate at low SNR when Gray coding is used. It shares spectral efficiency with 4-QAM and can outperform 4-QAM or 16-QAM in very noisy channels. QPSK is widely used in practical wireless systems, often alongside QAM in adaptive modulation schemes [Read more...]   MATLAB Code clear all; close all; % Set parameters for QAM snr_dB = -20:2:20; % SNR values in dB qam_orders = [4, 16, 64, 256]; % QAM modulation orders % Loop through each QAM order and calculate theoretical BER figure; for qam_order = qam_orders     % Calculate theoretical BER using berawgn for QAM     ber_qam = berawgn(snr_dB, 'qam', qam_order);     % Plot the results for QAM     semilogy(snr_dB, ber_qam, 'o-', 'DisplayName', sprintf('%d-QAM', qam_order));  ...
Read more

Constellation Diagrams of ASK, PSK, and FSK

๐Ÿ“˜ Overview ๐Ÿงฎ Simulator for constellation diagrams of ASK, FSK, and PSK ๐Ÿงฎ Theory ๐Ÿงฎ MATLAB Codes ๐Ÿ“š Further Reading BASK (Binary ASK) Modulation: Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1.    BFSK (Binary FSK) Modulation: Transmits one of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals: +√Eb​ or -√Eb (they differ by 180 degree phase shift), where Eb​ is the energy per bit. These signals represent binary 0 and 1.    Simulator for BASK, BPSK, and BFSK Constellation Diagrams SNR (dB): 15 Add A...
Read more

Differences between Baseband and Passband Modulation Techniques

๐Ÿ“˜ Overview ๐Ÿงฎ Difference betwen baseband and passband ๐Ÿงฎ Baseband modulation techniques ๐Ÿงฎ Passband modulation techniques ๐Ÿ“š Further Reading   1. Frequency Translation Baseband Modulation: The signal occupies the lower end of the frequency spectrum, close to DC (0 Hz). Noise at these frequencies (such as 1/f noise or flicker noise) can significantly impact the signal.  Passband Modulation: The signal is shifted to a higher frequency range by modulating it with a carrier frequency. This translation can help to avoid low-frequency noise and interference, which are often more prevalent and stronger in the baseband. 2. Bandpass Filtering Baseband Modulation: The filtering of baseband signals is often limited by the need to preserve the low-frequency components of the signal. This makes it difficult to filter out low-frequency noise effectively. Passband Modulation: The modulated signal can be passed through a bandpass filter centered around t...
Read more

Theoretical BER vs SNR for binary ASK and FSK

๐Ÿ“˜ Overview & Theory ๐Ÿงฎ MATLAB Codes ๐Ÿ“š Further Reading Theoretical Ber vs SNR for Amplitude Shift Keying (ASK) The theoretical bit error rate (BER) for binary Amplitude Shift Keying (ASK) as a function of the signal-to-noise ratio (SNR) can be derived using the following expression: If we map the binary signals to 1 and -1 in ASK , the probability of bit error will be: BER = Q(√(2*SNR))   If we map the binary signals to 0 and 1 in ASK , the probability of bit error will be:    BER = Q(√(SNR/2))   Where: Q(x) is the Q-function, which is the tail probability of the standard normal distribution. SNR is the signal-to-noise ratio. N0 is the noise power spectral density. Where Q is the Q function In mathematics Q(x) = 0.5 * erfc(x/ √ 2)   Calculate the Probability of Error using Q-function for ASK: For ASK with amplitudes 0 and 1 : When bit '0' is transmitted, the received signal is noise only . When bit '1' is transmitted, the re...
Read more

MATLAB Code for Pulse Amplitude Modulation (PAM) and Demodulation

๐Ÿ“˜ Overview ๐Ÿงฎ MATLAB Code 1 ๐Ÿงฎ MATLAB Code 2 ๐Ÿงฎ MATLAB Code for Pulse Amplitude Modulation and Demodulation of Digital data ๐Ÿงฎ Other Pulse Modulation Techniques (e.g., PWM, PPM, DM, and PCM) ๐Ÿ“š Further Reading   Pulse Amplitude Modulation (PAM) & Demodulation MATLAB Script clc; clear all; close all; fm= 10; % frequency of the message signal fc= 100; % frequency of the carrier signal fs=1000*fm; % (=100KHz) sampling frequency (where 1000 is the upsampling factor) t=0:1/fs:1; % sampling rate of (1/fs = 100 kHz) m=1*cos(2*pi*fm*t); % Message signal with period 2*pi*fm (sinusoidal wave signal) c=0.5*square(2*pi*fc*t)+0.5; % square wave with period 2*pi*fc s=m.*c; % modulated signal (multiplication of element by element) subplot(4,1,1); plot(t,m); title('Message signal'); xlabel ('Time'); ylabel('Amplitude'); subplot(4,1,2); plot(t,c); title('Carrier signal'); xlabel('Time'); ylabel('Amplitude'); sub...
Read more