A novel detector based on the compact genetic algorithm for MIMO systems

Multiple-Input Multiple-Output (MIMO) wireless communication systems have attracted recently a lot of research attention due to their potential to increase the communication throughput and capacity. The minimum Bit Error Rate performance (BER) can be achieved using the Maximum Likelihood (ML) search based detection, but it's computationally impractical for large MIMO systems and higher order modulation. The compact Genetic Algorithm (cGA) is a powerful search technique that is used successfully to solve many problems in various disciplines. In this paper, we propose a new MIMO detector based on the compact GA as well as a second version based on the persistent elitist compact GA, we use a hybridization between them and the soft output of the Minimum Mean Square Error (MMSE) at the level of the initialization of the probability vector. Simulation results show that our proposal can achieve the performance of ML detector for MIMO systems with a reduced computing time.