- This example uses a simple AWGN channel. In practice, consider more complex channel models for a realistic scenario.
- In practical RSMA systems, decoding strategies may involve SIC (Successive Interference Cancellation) or other techniques to efficiently separate common and private messages. Refer to following MATLAB answer to learn more about implementing SIC in MATLAB: https://www.mathworks.com/support/search.html/answers/483538-matlab-code-for-sic-successive-interference-cancellation-at-receiver.html
RSMA in wireless communication
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Hello,
Anyone has basic MATLAB code upon RSMA i.e. to understand basic implementation of RSMA, how to generate common and private messages in MATLAB, etc...?
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Answers (1)
Saurav
on 24 Dec 2024
Edited: Saurav
on 24 Dec 2024
You can refer to the following MATLAB answer to gain a basic understanding and implementation of RSMA.
RSMA is a promising communication strategy that allows for more efficient spectrum usage by splitting user messages into common and private parts. This technique can enhance data rates and reliability in wireless networks.
Below is a simple example that provides a basic framework to understand the RSMA concept. For more detailed implementations, consider exploring specific RSMA algorithms and optimizations in research literature.
% Parameters
numUsers = 2; % Number of users
msgLength = 1000; % Length of the message
modOrder = 4; % QPSK modulation
snr = 0; % Signal-to-noise ratio in dB
% Power allocation factors (summing to 1)
powerCommon = 0.5; % Power allocated to common message
powerPrivate = 0.25; % Power allocated to each private message
% Generate random binary messages for each user
user1_msg = randi([0, 1], msgLength, 1);
user2_msg = randi([0, 1], msgLength, 1);
% Split messages into common and private parts
common_msg = xor(user1_msg(1:msgLength/2), user2_msg(1:msgLength/2));
private_msg_user1 = user1_msg(msgLength/2+1:end);
private_msg_user2 = user2_msg(msgLength/2+1:end);
% Modulate messages using QPSK
modulator = comm.QPSKModulator('BitInput', true);
common_mod = modulator(common_msg);
% Release the modulator to allow reuse
release(modulator);
private_mod_user1 = modulator(private_msg_user1);
release(modulator);
private_mod_user2 = modulator(private_msg_user2);
% Apply power allocation
common_mod = common_mod * sqrt(powerCommon);
private_mod_user1 = private_mod_user1 * sqrt(powerPrivate);
private_mod_user2 = private_mod_user2 * sqrt(powerPrivate);
% Combine modulated signals for transmission
transmitted_signal_user1 = [common_mod; private_mod_user1];
transmitted_signal_user2 = [common_mod; private_mod_user2];
% Add noise to the transmitted signals
rx_signal_user1 = awgn(transmitted_signal_user1, snr, 'measured');
rx_signal_user2 = awgn(transmitted_signal_user2, snr, 'measured');
% Demodulate received signals
demodulator = comm.QPSKDemodulator('BitOutput', true);
received_common_msg = demodulator(rx_signal_user1(1:length(common_mod)));
received_private_msg_user1 = demodulator(rx_signal_user1(length(common_mod)+1:end));
received_private_msg_user2 = demodulator(rx_signal_user2(length(common_mod)+1:end));
% Reconstruct original messages
reconstructed_user1_msg = [received_common_msg; received_private_msg_user1];
reconstructed_user2_msg = [received_common_msg; received_private_msg_user2];
% Calculate Bit Error Rate (BER)
ber_user1 = sum(user1_msg ~= reconstructed_user1_msg) / msgLength;
ber_user2 = sum(user2_msg ~= reconstructed_user2_msg) / msgLength;
fprintf('User 1 BER: %.2f%%\n', ber_user1 * 100);
fprintf('User 2 BER: %.2f%%\n', ber_user2 * 100);
Additional Considerations:
Hope this helps!
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