Modified inertia weight approach in PSO algorithm to enhance MMSE Equalization

The need of effective adaptive algorithm with faster convergence rate for rapid time changing channel requires innovative, simple algorithmic improvement in channel equalization. The simple and fast Particle Swarm Optimization (PSO) algorithm provides promising results in equalization under all channel varying conditions. To balance the exploitation and exploration characteristics, the innovative inertia weight parameter selection is demanded. This work proposes a new method including fuzzy complements inertia weight strategy which shows superior performance. The performance is validated through extensive simulations for different inertia weight strategies. Further the simulation result examines the Minimum Mean Square Error (MMSE) on different channel conditions.