Estimation of carrier frequency offsets for uplink OFDMA system using a hybrid Taguchi-mutated-particle swarm optimization approach

In orthogonal frequency division multiple access (OFDMA) uplink systems, carrier frequency offsets (CFOs) caused by multiple users may significantly degrade system performance. Therefore, many approaches have recently been proposed to estimate the CFOs, such as Simplified Maximum Likelihood (SML) Scheme and Fast Algorithm. While those algorithms reveal acceptable performance, their computational burdens are still very high. For reducing the computational burden, a new particle swarm optimization (PSO)-based scheme is proposed in this study by introducing the mutation operation and Taguchi method. Experimental results indicate that the proposed approach can achieve performance close to SML and Fast Algorithm with much less computational burden.