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has been cited by the following article:

• TITLE: A PTS Optimization Scheme with Superimposed Training for PAPR Reduction in OFDM System

  AUTHORS: Renze Luo, Rui Li, Xiaoqiong Wu, Shuainan Hu, Na Niu

  KEYWORDS: Orthogonal Frequency Division Multiplexing (OFDM), Peak-to-Average Power Ratio (PAPR), Partial Transmit Sequences (PTS), Superimposed Training

  JOURNAL NAME: Communications and Network, Vol.6 No.2, May 13, 2014

  ABSTRACT: Partial Transmit Sequences (PTS) is an efficient scheme for Peak-to-Average Power Ratio (PAPR) reduction in Orthogonal Frequency Division Multiplexing (OFDM) system. It does not bring any signal distortion. However, its remarkable drawback is the high computational complexity. In order to reduce the computational complexity, currently many PTS methods have been proposed but with the cost of the loss of PAPR performance of the system. In this paper, we introduce an improved PTS optimization method with superimposed training. Simulation results show that, compared with conventional PTS, improved PTS scheme can achieve better PAPR performance while be implemented with lower computation complexity of the system.