Joint Symbol Detection Algorithm for Multi-antenna Signals over Flat-fading Channels Based on Variational Bayes

Kai ZHANG; Yao TIAN; Yunpeng XIE; Yi LIU

doi:10.11999/JEIT180073

Volume 40 Issue 9

Aug. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(9): 2096-2104

Kai ZHANG, Yao TIAN, Yunpeng XIE, Yi LIU. Joint Symbol Detection Algorithm for Multi-antenna Signals over Flat-fading Channels Based on Variational Bayes[J]. Journal of Electronics & Information Technology, 2018, 40(9): 2096-2104. doi: 10.11999/JEIT180073

Citation:

Kai ZHANG, Yao TIAN, Yunpeng XIE, Yi LIU. Joint Symbol Detection Algorithm for Multi-antenna Signals over Flat-fading Channels Based on Variational Bayes[J]. Journal of Electronics & Information Technology, 2018, 40(9): 2096-2104. doi: 10.11999/JEIT180073

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Joint Symbol Detection Algorithm for Multi-antenna Signals over Flat-fading Channels Based on Variational Bayes

doi: 10.11999/JEIT180073

Kai ZHANG^{1
,
,},
Yao TIAN²,
Yunpeng XIE¹,
Yi LIU¹

1.
Luoyang Electronic Equipment Test Center of China, Luoyang 471000, China
2.
96862 Troops, Luoyang 471000, China

Funds: The National Natural Science Foundation of China (61501517)

Received Date: 2018-01-19
Rev Recd Date: 2018-06-27

Available Online: 2018-07-12

Publish Date: 2018-09-01

Abstract

Abstract

For the issue of joint parameter estimation and symbol detection for multi-antenna signals with channel parameters difference over flat-fading channels, a new joint processing scheme is proposed based on the Variational Bayes (VB) method. The proposed scheme uses directly multiple received signals for the estimation of information symbols, restraining the information loss in conventional decoupled scheme of signals combination and demodulation. The problem is modeled as the joint Maximum A Posteriori (MAP) estimation of information symbols, time-delays, complex channel gains, and noise powers, given multiple observations, and approximately solved by means of VB approach. Based on the criterion of minimum relative entropy, analytical-form of the approximate distributions, i.e., variational distributions, for all unknown parameters are derived. There is no need to determine accurate point estimates of the parameters. Instead, the proposed scheme proceeds iteratively by alternating between the variational distributions of channel parameters and the information symbols. Simulation results show that the proposed joint processing scheme has significant performance improvements in comparison with conventional decoupled or partly joint processing schemes especially with large array sizes and short signal lengths.
- Multi-antenna arraying,
- Flat-fading,
- Joint processing,
- Variational Bayes

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References(23)

References

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