A novel generalized oppositional biogeography-based optimization algorithm: application to peak to average power ratio reduction in OFDM systems
A major drawback of orthogonal frequency division multiplexing (OFDM) signals is the high value of peak to average power ratio (PAPR). Partial transmit sequences (PTS) is a popular PAPR reduction method with good PAPR reduction performance, but its search complexity is high. In this paper, in order to reduce PTS search complexity we propose a new technique based on biogeography-based optimization (BBO). More specifically, we present a new Generalized Oppositional Biogeography Based Optimization (GOBBO) algorithm which is enhanced with Oppositional Based Learning (OBL) techniques. We apply both the original BBO and the new Generalized Oppositional BBO (GOBBO) to the PTS problem. The GOBBO-PTS method is compared with other PTS schemes for PAPR reduction found in the literature. The simulation results show that GOBBO and BBO are in general highly efficient in producing significant PAPR reduction and reducing the PTS search complexity.
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