Low-complexity joint channel estimation and symbol detection for OFDMA systems

In this paper, we propose a joint channel estimation and symbol detection (JCESD) algorithm relying on message-passing algorithms (MPA) for orthogonal frequency division multiple access (OFDMA) systems. The channel estimation and symbol detection leverage the framework of expectation propagation (EP) and belief propagation (BP) with the aid of Gaussian approximation, respectively. Furthermore, to reduce the computation complexity involved in channel estimation, the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula. Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%, compared with the traditional linear minimum mean square error (LMMSE) algorithm, and can approach to the bit error rate (BER) performance bound of perfectly known channel state information within 0.1 dB.

[1]  Zhigang Cao,et al.  Analysis of low-complexity windowed DFT-based MMSE channel estimator for OFDM systems , 2001, IEEE Trans. Commun..

[2]  Loïc Brunel,et al.  Joint channel estimation and decoding using Gaussian approximation in a factor graph over multipath channel , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

[3]  Zhongming Zheng,et al.  LTE-unlicensed: the future of spectrum aggregation for cellular networks , 2015, IEEE Wireless Communications.

[4]  O. Edfors,et al.  OFDM channel estimation by singular value decomposition , 1996, Proceedings of Vehicular Technology Conference - VTC.

[5]  Jianhua Lu,et al.  An Expectation Propagation Perspective on Approximate Message Passing , 2015, IEEE Signal Processing Letters.

[6]  Jianhua Lu,et al.  Expectation propagation approach to joint channel estimation and decoding for OFDM systems , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[7]  Fei Zheng,et al.  Distributed energy saving mechanism based on CoMP in LTE-A system , 2016, China Communications.

[8]  Zhigang Cao,et al.  Channel estimation for OFDM transmission in multipath fading channels based on parametric channel modeling , 2001, IEEE Trans. Commun..

[9]  Srikrishna Bhashyam,et al.  Parametric Channel Estimation for Pseudo-Random Tile-Allocation in Uplink OFDMA , 2007, IEEE Transactions on Signal Processing.

[10]  Han Zhang,et al.  Linearly Time-Varying Channel Estimation and Symbol Detection for OFDMA Uplink Using Superimposed Training , 2009, EURASIP J. Wirel. Commun. Netw..

[11]  Gerhard Fettweis,et al.  Expectation Propagation for Near-Optimum Detection of MIMO-GFDM Signals , 2016, IEEE Transactions on Wireless Communications.

[12]  Hichem Besbes,et al.  The impact of the superposition coding concept on admission control strategy in OFDMA-based network , 2018, China Communications.

[13]  Jianhua Lu,et al.  Low-Complexity Iterative Detection for Large-Scale Multiuser MIMO-OFDM Systems Using Approximate Message Passing , 2014, IEEE Journal of Selected Topics in Signal Processing.

[14]  Iuliana F Iatan The expectation-maximization algorithm: Gaussian case , 2010, 2010 International Conference on Networking and Information Technology.

[15]  Rahim Tafazolli,et al.  Channel Estimation for OFDMA Uplink: a Hybrid of Linear and BEM Interpolation Approach , 2007, IEEE Transactions on Signal Processing.

[16]  Heinrich Meyr,et al.  Optimum receiver design for OFDM-based broadband transmission .II. A case study , 2001, IEEE Trans. Commun..

[17]  Zhiyong Feng,et al.  Coexistence analysis between 5G system and fixed-satellite service in 3400–3600 MHz , 2018, China Communications.

[18]  Qinghua Guo,et al.  Low complexity sparse Bayesian learning using combined belief propagation and mean field with a stretched factor graph , 2016, Signal Process..

[19]  X. Jin Factor graphs and the Sum-Product Algorithm , 2002 .

[20]  C.-C. Jay Kuo,et al.  Joint maximum likelihood estimation of carrier frequency offset and channel in uplink OFDMA systems , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[21]  Di Zhao,et al.  Preconditioning Toeplitz-plus-diagonal linear systems using the Sherman-Morrison-Woodbury formula , 2017, J. Comput. Appl. Math..

[22]  P. Bianchi,et al.  Joint frequency offset and channel estimation in the OFDMA uplink: Cramer-Rao bounds and training sequence design , 2005, IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, 2005..

[23]  Yusuf Acar,et al.  Channel estimation for OFDM-IM systems , 2019, Turkish J. Electr. Eng. Comput. Sci..

[24]  Wei Feng,et al.  Fairness-oriented hybrid precoding for massive MIMO maritime downlink systems with large-scale CSIT , 2018, China Communications.

[25]  Dirk T. M. Slock,et al.  Performance analysis of general pilot-aided linear channel estimation in LTE OFDMA systems with application to simplified MMSE schemes , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[26]  Jianhua Lu,et al.  When mmWave Communications Meet Network Densification: A Scalable Interference Coordination Perspective , 2017, IEEE Journal on Selected Areas in Communications.

[27]  Vahid Vahidi,et al.  OFDM high speed train communication systems in 5G cellular networks , 2018, 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[28]  Shuangfeng Han,et al.  Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends , 2015, IEEE Communications Magazine.

[29]  Ha H. Nguyen,et al.  A Novel Iterative OFDMA Channel Estimation Technique for DOCSIS 3.1 Uplink Channels , 2017, IEEE Transactions on Broadcasting.

[30]  Sheng Wu,et al.  Block Expectation Propagation for Downlink Channel Estimation in Massive MIMO Systems , 2016, IEEE Communications Letters.

[31]  Liang Gu,et al.  5G Field Trials: OFDM-Based Waveforms and Mixed Numerologies , 2017, IEEE Journal on Selected Areas in Communications.

[32]  Alireza Bayesteh,et al.  SCMA Codebook Design , 2014, 2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall).