logo

SCIENCE CHINA Information Sciences, Volume 61, Issue 4: 042301(2018) https://doi.org/10.1007/s11432-016-9056-5

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

More info
  • ReceivedOct 18, 2016
  • AcceptedMar 21, 2017
  • PublishedNov 20, 2017

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.


Funded by

National Natural Science Foundation of China(61471037)

National Natural Science Foundation of China(61571041)


Acknowledgment

Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 61471037, 61571041).


References

[1] Benedetto S, Garello R, Montorsi G, et al. MHOMS: high-speed ACM modem for satellite applications. IEEE Wirel Commun, 2005, 12: 66-77 Google Scholar

[2] Casini E, Gaudenzi R D, Ginesi A. DVB-S2 modem algorithms design and performance over typical satellite channels. Int J Satell Commun Netw, 2004, 22: 281-318 CrossRef Google Scholar

[3] Benedetto S, Biglieri E, Daffara R. Modeling and performance evaluation of nonlinear satellite links-a volterra series approach. IEEE Trans Aerosp Electron Syst, 1979, 4: 494-507 Google Scholar

[4] Karam G, Sari H. Analysis of predistortion, equalization, and ISI cancellation techniques in digital radio systems with nonlinear transmit amplifiers. IEEE Trans Commun, 1989, 37: 1245-1253 CrossRef Google Scholar

[5] Gutierrez A, Ryan W E. Performance of Volterra and MLSD receivers for nonlinear band-limited satellite systems. IEEE Trans Commun, 2000, 48: 1171-1177 CrossRef Google Scholar

[6] Malone J, Wickert J. Practical Volterra equalizers for wideband satellite communications with TWTA nonlinearities. In: Proceedings of Digital Signal Processing Workshop and IEEE Signal Processing Education Workshop, Sedona, 2011. 48--53. Google Scholar

[7] Deleu T, Horlin F, Dervin M. Turbo-equalization of the remaining interference in a pre-distorted non-linear satellite channel. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Florence, 2014. 1946--1950. Google Scholar

[8] Qian H, Yao S, Huang H, et al. A low-complexity digital predistortion algorithm for power amplifier linearization. IEEE Trans Broadcast, 2014, 60: 670-678 CrossRef Google Scholar

[9] Chen S, Tan S, Xu L, et al. Adaptive minimum error-rate filtering design: a review. Signal Process, 2008, 88: 1671-1697 CrossRef Google Scholar

[10] Cai Y, de Lamare R C. Space-time adaptive MMSE multiuser decision feedback detectors with multiple-feedback interference cancellation for CDMA systems. IEEE Trans Veh Tech, 2009, 58: 4129-4140 CrossRef Google Scholar

[11] Wu J, Zhong J, Cai Y, et al. New detection algorithms based on the jointly Gaussian approach and successive interference cancelation for iterative MIMO systems. Int J Commun Syst, 2014, 27: 1964-1983 CrossRef Google Scholar

[12] Xing C, Ma S, Zhou Y. Matrix-monotonic optimization for MIMO systems. IEEE Trans Signal Process, 2015, 63: 334-348 CrossRef Google Scholar

[13] Gong C, Xu Z. Channel estimation and signal detection for optical wireless scattering communication with inter-symbol interference. IEEE Trans Wirel Commun, 2015, 14: 5326-5337 CrossRef Google Scholar

[14] Xing C, Gao F, Zhou Y. A framework for transceiver designs for multi-hop communications with covariance shaping constraints. IEEE Trans Signal Process, 2015, 63: 3930-3945 CrossRef Google Scholar

[15] Zhou W, Zhang S. The decision delay in finite-length MMSE-DFE systems systems. Wirel Pers Commun, 2015, 83: 1-15 CrossRef Google Scholar

[16] Xing C, Ma Y, et al. Transceiver optimization for multi-hop communications with per-antenna power constraints. IEEE Trans Signal Process, 2016, 64: 1519-1534 CrossRef Google Scholar

[17] Huang G M, Gillin D, Zhou D, et al. An efficient and robust method to determine the optimal tap coefficients of high speed FIR equalizer. Sci China Inf Sci, 2017, 60: 022401-1534 CrossRef Google Scholar

[18] Muller R R, Gerstacker W H. On the capacity loss due to separation of detection and decoding. IEEE Trans Inf Theory, 2004, 50: 1769-1778 CrossRef Google Scholar

[19] Douillard C, Jezequel M, Berrou C. Iterative correction of intersymbol interference: turbo equalization. Eur Trans Telecommun, 1995, 6: 507-511 CrossRef Google Scholar

[20] Schlegel C B, Perez L C. Trellis and Turbo Coding: Iterative and Graph-Based Error Control Coding. Hoboken: John Wiley & Sons, 2015. Google Scholar

[21] Laot C, Glavieux A, Labat J. Turbo equalization: adaptive equalization and channel decoding jointly optimized. IEEE J Sel Areas Commun, 2001, 19: 1744-1752 CrossRef Google Scholar

[22] Reynolds D, Wang X. Low-complexity turbo-equalization for diversity channels. Signal Process, 2001, 81: 989-995 CrossRef Google Scholar

[23] Tuchler M, Koetter R, Singer A C. Turbo equalization: principles and new results. IEEE Trans Commun, 2002, 50: 754-767 CrossRef Google Scholar

[24] Zhong W, Lu A A, Gao X Q. MMSE SQRD based SISO detection for coded MIMO-OFDM systems. Sci China Inf Sci, 2014, 57: 042311-767 Google Scholar

[25] Liu L, Leung W, Ping L. Simple iterative chip-by-chip multiuser detection for CDMA systems. In: Proceedings of IEEE Vehicular Technology Conference, Jeju Island, 2003. 2157--2161. Google Scholar

[26] Guo Q, Ping L. LMMSE turbo equalization based on factor graphs. IEEE J Sel Areas Commun, 2008, 26: 311-319 CrossRef Google Scholar

[27] Kashif F M, Wymeersch H, Win M Z. Monte carlo equalization for nonlinear dispersive satellite channels. IEEE J Sel Areas Commun, 2008, 26: 245-255 CrossRef Google Scholar

[28] Benedetto S, Biglieri E. Nonlinear equalization of digital satellite channels. IEEE J Sel Areas Commun, 1983, 1: 57-62 CrossRef Google Scholar

[29] Chen Y C, Su Y T. Turbo equalization of nonlinear TDMA satellite signals. IEICE Trans Commun, 2009, 92: 992-997 Google Scholar

[30] Burnet C E, Cowley W G. Performance analysis of turbo equalization for nonlinear channels. In: Proceedings of International Symposium on Information Theory, Adelaide, 2005. 2026--2030. Google Scholar

[31] Ampeliotis D, Rontogiannis A, et al. Turbo equalization of non-linear satellite channels using soft interference cancellation. Adv Sat Mobile Syst, 2008, 124: 289-292 Google Scholar

[32] Benammar B, Thomas N, Poulliat C, et al. On linear MMSE based turbo-equalization of nonlinear volterra channels. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, Vancouver, 2013. 4703--4707. Google Scholar

[33] Wang X, Poor H V. Iterative (turbo) soft interference cancellation and decoding for coded CDMA. IEEE Trans Commun, 1999, 47: 1046-1061 CrossRef Google Scholar

[34] Xing C, Ma S, Wu Y C. Robust joint design of linear relay precoder and destination equalizer for dual-hop amplify-and-forward MIMO relay systems. IEEE Trans Signal Process, 2010, 58: 2273-2283 CrossRef Google Scholar

[35] Tuchler M, Singer A C. Turbo equalization: an overview. IEEE Trans Inf Theory, 2011, 57: 920-952 CrossRef Google Scholar

[36] Liu L, Ping L. An extending window MMSE turbo equalization algorithm. IEEE Signal Process Lett, 2004, 11: 891-894 CrossRef Google Scholar

Copyright 2020 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1       京公网安备11010102003388号