Adaptive Population Sizing Genetic Algorithm Assisted Maximum Likelihood Detection of OFDM Symbols in the Presence of Nonlinear Distortions

In this paper, the author’s present Adaptive population sizing Genetic Algorithm (AGA) assisted Maximum Likelihood (ML) estimation of Orthogonal Frequency Division Multiplexing (OFDM) symbols in the presence of nonlinear distortions. The proposed algorithm is simulated in MATLAB and compared with existing estimation algorithms such as iterative DAR, decision feedback clipping removal, iteration decoder, Genetic Algorithm (GA) assisted ML estimation and theoretical ML estimation. Simulation results proved that the performance of the proposed AGA assisted ML estimation algorithm is superior compared with the existing estimation algorithms.

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