A Hybrid BP-EP-VMP Approach to Joint Channel Estimation and Decoding for FTN Signaling over Frequency Selective Fading Channels

This paper deals with low-complexity joint channel estimation and decoding for faster-than-Nyquist (FTN) signaling over frequency selective fading channels. The inter-symbol interference (ISI) imposed by FTN signaling and the frequency selective channel are intentionally separated to fully exploit the known structure of the FTN-induced ISI. Colored noise due to the faster sampling rate than that of the Nyquist signaling system is approximated by autoregressive process. A Forney style factor graph representation of the FTN system is developed and Gaussian message passing is performed on the graph. Expectation propagation (EP) is employed to approximate the message from channel decoder to Gaussian distribution. Since the inner product between FTN symbols and channel coefficients is infeasible by belief propagation (BP), we propose to perform variational message passing (VMP) on an equivalent soft node in factor graph to tackle this problem. Simulation results demonstrate that the proposed low-complexity hybrid BP-EP-VMP algorithm outperforms the existing methods in FTN system. Compared with the Nyquist counterpart, FTN signaling with the proposed algorithm is able to increase the transmission rate by over 40%, with only negligible BER performance loss. Disciplines Engineering | Science and Technology Studies Publication Details N. Wu, W. Yuan, Q. Guo & J. Kuang, "A Hybrid BP-EP-VMP Approach to Joint Channel Estimation and Decoding for FTN Signaling over Frequency Selective Fading Channels," IEEE Access, vol. 5, pp. 6849-6858, 2017. This journal article is available at Research Online: https://ro.uow. edu.au/eispapers1/258 Received April 17, 2017, accepted May 4, 2017, date of publication May 9, 2017, date of current version June 7, 2017. Digital Object Identifier 10.1109/ACCESS.2017. 2702571 A Hybrid BP-EP-VMP Approach to Joint Channel Estimation and Decoding for FTN Signaling over Frequency Selective Fading Channels NAN WU1, (Member, IEEE), WEIJIE YUAN1, (Student Member, IEEE), QINGHUA GUO2,3, (Member, IEEE), AND JINGMING KUANG1 1School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China 2School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia 3School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA 6009, Australia Corresponding author: Nan Wu (wunan@bit.edu.cn) This work was supported in part by the National Science Foundation of China under Grant 61421001, Grant 61571041, and Grant 61471037, in part by the National High Technology Research and Development Program of China under Grant 2015AA01A709, and in part by the Australian Research Council’s DECRA under Grant DE120101266. ABSTRACT This paper deals with low-complexity joint channel estimation and decoding for faster-thanNyquist (FTN) signaling over frequency selective fading channels. The inter-symbol interference (ISI) imposed by FTN signaling and the frequency selective channel are intentionally separated to fully exploit the known structure of the FTN-induced ISI. Colored noise due to the faster sampling rate than that of the Nyquist signaling system is approximated by autoregressive process. A Forney style factor graph representation of the FTN system is developed and Gaussian message passing is performed on the graph. Expectation propagation (EP) is employed to approximate the message from channel decoder to Gaussian distribution. Since the inner product between FTN symbols and channel coefficients is infeasible by belief propagation (BP), we propose to perform variational message passing (VMP) on an equivalent soft node in factor graph to tackle this problem. Simulation results demonstrate that the proposed low-complexity hybrid BP-EP-VMP algorithm outperforms the existing methods in FTN system. Compared with the Nyquist counterpart, FTN signaling with the proposed algorithm is able to increase the transmission rate by over 40%, with only negligible BER performance loss.This paper deals with low-complexity joint channel estimation and decoding for faster-thanNyquist (FTN) signaling over frequency selective fading channels. The inter-symbol interference (ISI) imposed by FTN signaling and the frequency selective channel are intentionally separated to fully exploit the known structure of the FTN-induced ISI. Colored noise due to the faster sampling rate than that of the Nyquist signaling system is approximated by autoregressive process. A Forney style factor graph representation of the FTN system is developed and Gaussian message passing is performed on the graph. Expectation propagation (EP) is employed to approximate the message from channel decoder to Gaussian distribution. Since the inner product between FTN symbols and channel coefficients is infeasible by belief propagation (BP), we propose to perform variational message passing (VMP) on an equivalent soft node in factor graph to tackle this problem. Simulation results demonstrate that the proposed low-complexity hybrid BP-EP-VMP algorithm outperforms the existing methods in FTN system. Compared with the Nyquist counterpart, FTN signaling with the proposed algorithm is able to increase the transmission rate by over 40%, with only negligible BER performance loss. INDEX TERMS Faster-than-Nyquist signaling, factor graph, joint channel estimation and decoding, belief propagation, variational message passing, expectation propagation.