The orthogonal frequency division multiplexing (OFDM) modulation technique is one of the key strategies for multiuser signal transmission especially in smart grids and wind farms. This paper introduces an approach for peak-to-average power ratio (PAPR) reduction of such signals based on novel global harmony search (NGHS) and partial transmit sequence (PTS) schemes. In PTS technique, the data block to be transmitted is partitioned into disjoint subblocks, which are combined using phase factors to minimize PAPR. The PTS requires an exhaustive search over all combinations of allowed phase factors. Therefore, with respect to the fast implementation and simplicity of NGHS technique, we could achieve significant reduction of PAPR. 1. Introduction Orthogonal frequency division multiplexing (OFDM) is an attractive technology for high-bit-rate transmission in wireless communications and has been widely adopted in different communication applications such as smart grid communication systems and offshore wind farms (OWFs) for data transmission between wind turbines [1]. However, some challenging issues still remain unsolved in design of such systems. One critical problem is large peak-to-average power ratio (PAPR) of the transmitted signals, which requires power amplifiers with a large linear range. Therefore, the OFDM receiver’s detection is very sensitive to the nonlinear devices [2]. Over the past decade, various PAPR reduction techniques have been proposed in the literature [2]. One type of PAPR reduction methods is the probabilistic scheme; such as partial transmit sequence (PTS) technique that is based on combining signal subblocks which are phase-shifted by constant phase factors [3]. Another probabilistic scheme is selective mapping (SLM) in which multiple sequences with the lowest PAPR are transmitted [2]. PTS technique can get side information, which is needed to be sent at the same time and is able to achieve sufficient PAPR reduction [3]. However, the continuous search complexity of the optimal phase combination increases exponentially with the number of subblocks. Suboptimal PTS methods are of interest in the literature [4]. The iterative flipping PTS (IPTS) in [5] has linearly proportional computational complexity to the number of subblocks. A systematic procedure for the minimum error probability to look for and form the optimal precoding matrices is proposed in [6]. In exhaustive search of phase factors, the computational complexity increases exponentially with the number of the subblocks. Therefore, a scheme is proposed in [7] by utilizing the
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