A Low-complexity Algorithm for Joint Channel Estimation in Two-way MIMO Relay Communication Systems

DU Jianhe; HUA Yan; LIN Heyun; TIAN Pei

doi:10.11999/JEIT170463

Volume 39 Issue 12

Dec. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(12): 2976-2982

DU Jianhe, HUA Yan, LIN Heyun, TIAN Pei. A Low-complexity Algorithm for Joint Channel Estimation in Two-way MIMO Relay Communication Systems[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2976-2982. doi: 10.11999/JEIT170463

Citation:

DU Jianhe, HUA Yan, LIN Heyun, TIAN Pei. A Low-complexity Algorithm for Joint Channel Estimation in Two-way MIMO Relay Communication Systems[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2976-2982. doi: 10.11999/JEIT170463

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A Low-complexity Algorithm for Joint Channel Estimation in Two-way MIMO Relay Communication Systems

doi: 10.11999/JEIT170463

1.
(School of Information and Engineering, Communication University of China, Beijing 100024, China)
2.
(School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Funds:

The National Natural Science Foundation of China (61601414, 61561037), The National High Technology Research and Development Program of China (2015AA01A705, 2014AA01A701)

Received Date: 2017-05-16
Rev Recd Date: 2017-09-16
Publish Date: 2017-12-19

Abstract

Abstract

For two-way Multiple-Input Multiple-Output (MIMO) relay communication systems, the main challenge is to get full knowledge of all channel matrices with minimal cost of signal handling at the relay node. In this paper, a low-complexity joint channel estimation scheme for two-way MIMO relay communication systems is proposed. Both users transmit orthogonal channel training signals to the relay node simultaneously. Then the relay amplifies the received signals by using designed amplification factors, and forwards the amplified signals to both users. The received signals at each user is formulated as a PARAllel FACtor (PARAFAC) model, and then the iterative and non-iterative fitting algorithms are derived to estimate the Channel State Information (CSI) knowledge of all links involved. Compared with existing schemes, the proposed scheme has the advantages of design flexibility and low complexity, and has higher estimation accuracy with a few number of channel training signals.
- Two-way MIMO relay,
- Low-complexity,
- Channel State Information (CSI),
- Parallel factor

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References(21)

References

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