Turbo equalization based on joint Gaussian, SIC-MMSE and LMMSE for nonlinear satellite channels

Zheren Long, Hua Wang*, Nan Wu, Jingming Kuang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The nonlinear distortion of wideband signal due to the filtering and efficiently operated high power amplifiers limits the performance of satellite communications. Volterra series can be used to describe the nonlinear satellite channels effectively. Most existing equalizers simply ignore the nonlinear terms or treat all the nonlinear combinations of symbols as interference. In this study, by properly exploiting information from nonlinear terms, we propose three turbo equalizers for nonlinear satellite channels, namely, joint Gaussian (JG), soft interference cancellation-minimum mean square error (SIC-MMSE) and linear minimum mean square error (LMMSE) equalizers. In JG and SIC-MMSE-based equalizers, both the linear and nonlinear terms that contain the symbol of interest are considered as desired signals. Accordingly, the required statistics are calculated based on the a priori probabilities of coded bits from output of channel decoder. For LMMSE-based equalizer, we propose to calculate the extrinsic information from output of equalizer by excluding the prior information in both the linear and nonlinear terms. Simulation results demonstrate that the proposed equalizers significantly outperform the method which ignores the presence of nonlinear interferences. Moreover, the nonlinear terms that contain the symbol of interest can be exploited to further improve the performance of turbo equalization.

Original languageEnglish
Article number042301
JournalScience China Information Sciences
Volume61
Issue number4
DOIs
Publication statusPublished - 1 Apr 2018

Keywords

  • joint Gaussian
  • linear minimum mean square error (LMMSE)
  • nonlinear satellite channel
  • soft interference cancellation-minimum mean square error (SIC-MMSE)
  • turbo equalization

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