OFDM Channel Estimation Based on Novel Local Search Particle Swarm Optimization Algorithm

Abstract

A novel Channel Estimation (CE) approach in multi-carrier wireless communication systems, such as Orthogonal Frequency Division Multiplexing (OFDM) system and Code Division Multiple access (CDMA) via a combination of Local Search (LS) and Particle Swarm Optimization (PSO) algorithm is proposed in this study. The CE is vital towards overcoming the effect of channel fading, which causes the degradation of the Bit Error Rate (BER) and the jamming of pilot symbols. The CE expressions were derived as an objective function to study the effect of improving BER in MC-CDMA/OFDM for a frequency selective Rayleigh fading environment. The number of particles for each single swarm was used to determine the best fitness solution, and is being computed from an average BER value. The proposed channel estimator was tested under the fast fading channel in a multi carrier communication system with and without interpolation methods. The simulation showed that the proposed CE of the MIMO-OFDM system can significantly result in better BER performance compared with other techniques at different modulation types, mean square error (MSE), Signal-to-Noise Ratio (SNR) values, and channel lengths.