Self-adapting Particle Swarm Optimization for signal detection in LTE system

This paper proposed a novel algorithm based on self-adapting Particle Swarm Optimization (PSO) for signal detection in Long Term Evolution (LTE) system. LTE system is equipped with Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) technology, which have been widely applied in advanced communication systems for reducing fading and increasing channel capacity. Earlier, efficient signal detection based on Swarm-Intelligence is performed. PSO is a heuristic algorithm simulating social behavior of animals. Its relatively low computational complexity and fast convergence make it suitable for signal detection. However, PSO is vulnerable to local optimum. This paper solved such problem by changing parameters simultaneously with Signal to Noise Ratio (SNR). Simulation result demonstrated new self-adapting PSO based detector achieves better performance than traditional detector in LTE system´s signal detection.