A NN Predistortion Method for Nonlinear HPAs in OFDM System

Cui Hua

doi:10.3724/SP.J.1146.2007.01483

Volume 31 Issue 6

Jun. 2009

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2009 > 31(6): 1451-1454

Cui Hua. A NN Predistortion Method for Nonlinear HPAs in OFDM System[J]. Journal of Electronics & Information Technology, 2009, 31(6): 1451-1454. doi: 10.3724/SP.J.1146.2007.01483

Citation:

Cui Hua. A NN Predistortion Method for Nonlinear HPAs in OFDM System[J]. Journal of Electronics & Information Technology, 2009, 31(6): 1451-1454. doi: 10.3724/SP.J.1146.2007.01483

Cui Hua. A NN Predistortion Method for Nonlinear HPAs in OFDM System[J]. Journal of Electronics & Information Technology, 2009, 31(6): 1451-1454. doi: 10.3724/SP.J.1146.2007.01483

Citation:

Cui Hua. A NN Predistortion Method for Nonlinear HPAs in OFDM System[J]. Journal of Electronics & Information Technology, 2009, 31(6): 1451-1454. doi: 10.3724/SP.J.1146.2007.01483

PDF( 255 KB)

A NN Predistortion Method for Nonlinear HPAs in OFDM System

doi: 10.3724/SP.J.1146.2007.01483 cstr: 32379.14.SP.J.1146.2007.01483

Cui Hua

Received Date: 2007-09-14
Rev Recd Date: 2009-04-23
Publish Date: 2009-06-19

Abstract

Abstract

To circumvent the transmission performance degradation of Orthogonal Frequency Division Multiplexing (OFDM) systems due to the nonlinear HPA, a new predistorter is presented to predistort HPA which consists of two similar single-input and single-output Neural Networks (NNs) in series. The former NN is the inverse model of HPAs AM-AM characteristics to compensate its amplitude and the latter the model of AM-PM characteristics to compensate its phase. The phase predistortion is implemented just by its model rather its inverse model, which ensures it of much higher precision. Simulation results show that even though input back-off is as low as 2.93dB, the spectral regrowth can be reduced about 10dB. The proposed scheme can adaptively predistort HPA effectively and simply, and improve transmission performance of OFDM system greatly.

FullText(HTML)

References(1)

References

Van Nee R and Prasad R. OFDM for Wireless MultimediaCommunications. London: Artech House, 2000: 33-250.[2]Lim Sunmin and Eun Changsoo. Predistorter design for amemoryless nonlinear high power amplifier using thepth-order inverse method for OFDM systems. Proc IEEE onIntelligent Signal Processing and Communication Systems,Hong Kong, 2005: 217-220.[3]Eun C and Powers E J. A new volterra predistorter based onthe indirect learning architecture[J].IEEE Trans. on SignalProcessing.1997, 45(1):223-227[4]Haykin S. Neural Networks, A Comprehensive Foundation.Second Edition. Englewood Cliffs, NJ: Prentice-Hall, 1999,Chap. 2-4.[5]Benvenuto N, Piazza F, and Uncini A. A neural networkapproach to data predistortion with memory in digital radiosystems[J].Proc. IEEE of ICC93 Intl. Conf. on Commun.,Geneva.1993, 1:232-236[6]Ibnkahla M. Neural network predistortion techniques fordigital satellite communications[J].Proc IEEE of ICASSP00,IEEE Computer Society, Istanbul.2000, 6:3506-3509[7]Qian Yeqing and Liu Fuqiang. Neural network predistortiontechnique for nonlinear power amplifiers with memory. ProcIEEE on Commun. and Networking, Beijing, 2006: 1-5.[8]Zou W and Wu Y. COFDM: An Overview[J].IEEE Trans. onBroadcasting.1995, 41(1):1-8[9]Ai Bo and Yang Zhixing. Effects of PAPR reduction on HPApredistorton[J].IEEE Trans. on Consumer Electronics.2005,51(4):1143-1147

Relative Articles

Supplements(0)

Cited By

Proportional views