Multiuser Detection in MIMO-OFDM Wireless Communication System Using Hybrid Firefly Algorithm

In recent years, future generation wireless communication technologies are most the prominent fields in which many innovative techniques are used for effective communication. Orthogonal frequency-division multiplexing is one of the important technologies used for communication in future generation technologies. Although it gives efficient results, it has some problems during the implementation in real-time. MIMO and OFDM are integrated to have both their benefits. But, noise and interference are the major issues in the MIMO OFDM systems. To overcome these issues multiuser detection method is used in MIMO OFDM. Several algorithms and mathematical formulations have been presented for solving multiuser detection problem in MIMO OFDM systems. The algorithms such as genetic simulated annealing algorithm, hybrid ant colony optimization algorithm are used for multiuser detection problem in previous studies. But, due to the limitations of those optimization algorithms, the results obtained are not significant. In this research, to overcome the noise and interference problems, hybrid firefly optimization algorithm based on the evolutionary algorithm is proposed. The proposed algorithm is compared with the existing multiuser detection algorithm such as particle swarm optimization, CEFM-GADA [complementary error function mutation (CEFM) and a differential algorithm (DA) genetic algorithm (GA)] and Hybrid firefly optimization algorithm based on evolutionary algorithm. The simulation results shows that performance of the proposed algorithm is better than the existing algorithm and it provides a satisfactory trade-off between computational complexity and detection performance Keywords--Multiple input multiple output, orthogonal frequency division multiplexing, firefly algorithm, genetic algorithm, particle swam optimization