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

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

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Southwest Petroleum University, Chengdu, Sichuan, China.
Zhongshan Branch China Telecom Co., Ltd., Zhongshan, Guangdong, China.

DOI: 10.4236/cn.2014.62012                

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.

Keywords

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

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Wu, Y.Y. and Zou, W.Y. (1995) Orthogonal Frequency Division Multiplexing: A Multi-Carrier Modulation Scheme. IEEE Transactions on Consumer Electronics, 41, 392-399. http://dx.doi.org/10.1109/30.468055
[2]	Han, S.H. and Lee, J.H. (2005) An Overview of Peak-to-Average Power Ratio Reduction Techniques for Multicarrier Transmission. IEEE Wireless Community, 12, 56-65. http://dx.doi.org/10.1109/MWC.2005.1421929
[3]	Wang, L. and Cao, Y. (2008) Sub-Optimum PTS for PAPR Reduction of OFDM Signals. IEEE Xplore: Electronics Letters, 44, 921-922.
[4]	Tugnai, J.K. and Luo, W. (2003) On Channel Estimation Using Superimposed Training and First-Order Statistics. IEEE Signal Processing Letters, 7, 413-415.
[5]	Telado, J. (2000) Multicarrier Modulation with Low PAR Applications to DSL and Wireless. Kluver Academic Publishers, Berlin.
[6]	Zhou, G.T., Viberg, M. and Mckelvey, T. (2003) A First-Order Statistical Method for Channel Estimation. IEEE Signal Processing Letters, 10, 57-60.
[7]	Orozco-Lugo, A.G., Lara, M.M. and Mclernon, D.C. (2004) Channel Estimation Using Implicit Trainging. IEEE Transactions on Signal Processing, 52, 240-254. http://dx.doi.org/10.1109/TSP.2003.819993
[8]	Nair, J.P., and Raja Kumar, R.V. (2006) Channel Estimation and Equalization Based on Implicit Training in OFDM Systems. IEEE Wireless and Optical Communications Networks, Bangalore.
[9]	Tugnait, J.K. and Meng, X.H. (2006) On Superimposed Training for Channel Estimation: Performance Analysis, Training Power Allocation, and Frame Synchronization. IEEE Transactions on Signal Processing, 54, 752-763. http://dx.doi.org/10.1109/TSP.2005.861749
[10]	He, S.C. and Tugnait, J.K. (2008) On Doubly Selective Channel Estimation Using Superimposed Training and Discrete Prolate Spheroidal Sequence. IEEE Transactions on Signal Processing, 56, 3214-3228.
[11]	Nair, J.P. and Raja Kumar, R.V (2008) An Iterative Channel Estimation Method Using Superimposed Training in OFDM Systems. IEEE VTC conference, Calgary, 21-24 September 2008, 1-5.