Hybrid Message Passing Algorithm for Downlink FDD Massive MIMO-OFDM Channel Estimation

The design of message passing (MP) algorithms on factor graphs is an effective manner to implement channel estimation (CE) in wireless communication systems, which performance can be further improved by exploiting prior probability models that accurately match the channel characteristics. In this wo...

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Veröffentlicht in:	IEEE transactions on wireless communications Jg. 23; H. 5; S. 4596 - 4609
Hauptverfasser:	Song, Yi, Zhang, Chuanzong, Lu, Xinhua, Saggese, Fabio, Wang, Zhongyong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Computational modeling Conditional probability Downlink Downlinking FDD channel estimation Linear functions Markov chains Markov processes Massive MIMO Message passing MIMO communication OFDM Orthogonal Frequency Division Multiplexing Probability density function Signal to noise ratio System effectiveness TSGM-LVD channel model Wireless communication Wireless communication systems
ISSN:	1536-1276, 1558-2248
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Abstract	The design of message passing (MP) algorithms on factor graphs is an effective manner to implement channel estimation (CE) in wireless communication systems, which performance can be further improved by exploiting prior probability models that accurately match the channel characteristics. In this work, we study the CE problem in a downlink massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. As the prior probability, we propose the Markov chain two-state Gaussian mixture with large variance differences (TSGM-LVD) model to exploit the structured sparsity in the angle-frequency domain of the channel. Existing single and combined MP rules cannot deal with the message computation of the proposed probability model. To overcome this issue, we present a general method to derive the hybrid message passing (HMP) rule, which allows the calculation of messages described by mixed linear and non-linear functions. Accordingly, we design the HMP-TSGM-LVD algorithm under the structured turbo framework (STF). Simulation results demonstrate that the proposed algorithm converges faster and obtains better and more stable performance than its counterparts. In particular, the gain of the proposed approach is maximum (3 dB) in the high signal-to-noise ratio regime, while benchmark approaches experience oscillating behavior due to the improper prior model characterization.
AbstractList	The design of message passing (MP) algorithms on factor graphs is an effective manner to implement channel estimation (CE) in wireless communication systems, which performance can be further improved by exploiting prior probability models that accurately match the channel characteristics. In this work, we study the CE problem in a downlink massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. As the prior probability, we propose the Markov chain two-state Gaussian mixture with large variance differences (TSGM-LVD) model to exploit the structured sparsity in the angle-frequency domain of the channel. Existing single and combined MP rules cannot deal with the message computation of the proposed probability model. To overcome this issue, we present a general method to derive the hybrid message passing (HMP) rule, which allows the calculation of messages described by mixed linear and non-linear functions. Accordingly, we design the HMP-TSGM-LVD algorithm under the structured turbo framework (STF). Simulation results demonstrate that the proposed algorithm converges faster and obtains better and more stable performance than its counterparts. In particular, the gain of the proposed approach is maximum (3 dB) in the high signal-to-noise ratio regime, while benchmark approaches experience oscillating behavior due to the improper prior model characterization.
Author	Lu, Xinhua Wang, Zhongyong Zhang, Chuanzong Song, Yi Saggese, Fabio
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Cites_doi	10.1109/MCOM.2010.5621984 10.1017/CBO9780511807213 10.1109/TWC.2019.2917905 10.1016/j.sigpro.2016.08.027 10.1109/TVT.2017.2787708 10.1002/wcs.72 10.1109/JIOT.2020.3038899 10.1109/TSP.2021.3114985 10.1109/ISIT.2012.6283939 10.1109/JSTSP.2014.2313020 10.1109/18.910572 10.1109/JSTSP.2011.2169232 10.1109/TWC.2018.2818142 10.1109/LSP.2016.2632180 10.1109/JSTSP.2014.2317671 10.1109/TWC.2016.2608342 10.1109/TWC.2021.3080923 10.1109/MCOM.2014.6736752 10.1109/LWC.2022.3152323 10.1109/TIT.2012.2218573 10.1109/TSP.2015.2463260 10.1109/ICC.2012.6363847 10.1109/TSP.2009.2020049 10.1109/LSP.2014.2351822 10.1109/TWC.2021.3056193 10.1109/TSP.2015.2446444 10.1109/LSP.2015.2414951 10.1109/TSP.2013.2272287 10.1109/ICC.2018.8422538 10.1109/TCOMM.2015.2508809 10.1109/ACCESS.2017.2697978 10.1073/pnas.0909892106 10.1109/TCOMM.2017.2691700 10.1007/s11235-018-0511-8
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References	ref13 ref35 ref12 ref34 ref15 ref37 ref14 ref36 ref30 ref11 ref33 ref10 ref2 ref1 ref17 ref39 ref16 ref38 ref19 Cui (ref28) 2017; 37 ref18 Zhang (ref29) 2017 Tipping (ref32) 2001; 1 ref24 ref26 ref25 ref20 ref21 ref27 ref8 ref7 Winn (ref22) 2005; 6 ref9 ref4 ref3 Minka (ref23) ref6 ref5 ref40 Salo (ref31) 2005
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SubjectTerms	Algorithms Computational modeling Conditional probability Downlink Downlinking FDD channel estimation Linear functions Markov chains Markov processes Massive MIMO Message passing MIMO communication OFDM Orthogonal Frequency Division Multiplexing Probability density function Signal to noise ratio System effectiveness TSGM-LVD channel model Wireless communication Wireless communication systems
Title	Hybrid Message Passing Algorithm for Downlink FDD Massive MIMO-OFDM Channel Estimation
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