In cooperative communication the effect of channel fading can be improved by
cooperation between the user terminals and the relay nodes in wireless
networks. In a Wireless Sensor Network (WSN), cooperative relaying improves
the link quality with a relatively high Energy Efficiency Gain (EEG). In
this paper, optimized parameters are used in WSN to enhance the EEG using
particle swarm optimization (PSO) and Real-Coded Genetic Algorithm (RGA).
Maximum enhancements of EEG obtained using RGA for M-ary Quadrature
Amplitude Modulation (M-QAM) is 64% for M=16, 87% for M=32, and 97% for M=64
compared to EEG obtained without optimization. The superiority proposed
optimization methods are verified by comparing with results without
optimization and by comparing with the published results for Energy
Efficiency (EE).