Hybrid Micro Genetic Algorithm Assisted Optimum Detector for Multi-Carrier Systems

Abstract

A low-complexity detection scheme, which consists of a Hybrid Micro Genetic Algorithm (Hybrid- µGA), is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems. In the absence of orthogonality, intercarrier-interference (ICI) occurs because a signal from one subcarrier causes interference to others. In several environment, the OFDM signal reflections from a far obstacle generate inter-block-interference (IBI) due to long time delays. To avoid these unpleasant effects of IBI and ICI in OFDM system, a Hybrid-µGA detection algorithm is proposed. The proposed detector combines the conventional one-Tap equalizer and the Micro Genetic Algorithm (µGA) search engine. The output of one-Tap equalizer is considered as the input to µGA search engine. Therefore, the µGA starts with some knowledge rather than blindly to speed up the search. Theoretical analysis and simulation results show that the proposed detection Hybrid- µGA scheme substantially improves the performance of OFDM systems. Moreover, its complexity is 10 times lower than the conventional GA.