MATLAB Implementation of Cooperative Diversity with Decode-and-Forward (DF)

Cooperative diversity technology serves as a critical method in wireless communications to enhance transmission reliability, where Decode-and-Forward (DF) stands as one of the classical relay cooperation modes. MATLAB simulation of the DF cooperative process enables intuitive performance analysis in multipath fading environments. The core DF cooperation mechanism operates in three phases: Broadcast Phase: The source node transmits signals to both relay and destination nodes, where receivers demodulate based on channel state information. Code implementation typically involves generating QPSK/QAM symbols and applying Rayleigh fading using functions like `rayleighchan`. Relay Decoding Phase: The relay node performs complete decoding of received signals (reconstructing if successful, discarding if failed) to prevent error propagation. This requires implementing a threshold-based decision logic, where the relay checks CRC or SNR thresholds using conditional statements like `if snr > threshold` before forwarding. Cooperative Forwarding Phase: The relay forwards decoded signals to the destination, where they combine with direct transmission from the source using Maximal Ratio Combining (MRC) to improve SNR. The MRC algorithm can be implemented through weighted summation based on channel gains. Key simulation components requiring modeling include: Rayleigh fading channel generation and noise addition using `awgn` function and random matrix generation Relay node threshold decision logic (determining forwarding conditions) through comparison operators Destination node signal combining and Bit Error Rate (BER) calculation via Monte Carlo simulation with error counting loops By comparing BER curves between DF cooperative and non-cooperative scenarios, diversity gain can be quantified. The simulation framework allows extensions for studying relay position optimization or integration with adaptive modulation strategies, where additional modules for distance-based path loss calculations and modulation index switching can be incorporated.