Joint channel estimation and multi-user detection for MC-CDMA system using genetic algorithm and simulated annealing

In multi-carrier code-division multiple-access (MC-CDMA) system the multiple access interference (MAI) is a critical factor that significantly degrades system performance. In this research the genetic algorithm (GA) is employed for joint channel estimation and multi-user detection. For improving exploration and exploitation strengths of GA, a GA-based approach called SAM-GA is developed by incorporating the simulated annealing (SA) to mutation operation. Furthermore, a threshold-based mutation is proposed to refine the SAM-GA scheme. The resulting scheme is called modified SAM-GA for simplicity. Experimental result demonstrates that the proposed modified SAM-GA scheme achieves the best performance in terms of mean squared error (MSE), bit error rate (BER), and convergence rate for joint CIR estimation and multi-user detection in the MC-CDMA system as compared to other schemes.