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Robust energy efficiency optimization for amplify-and-forward MIMO relaying systems

Robust energy efficiency optimization for amplify-and-forward MIMO relaying systems
Robust energy efficiency optimization for amplify-and-forward MIMO relaying systems
We investigate the energy efficiency (EE) of multiple-input multiple-output (MIMO) amplify-and-forward relaying networks relying on the realistic imperfect channel state information (CSI). Specifically, the relay jointly optimizes the source covariance and relay beamforming matrices by maximizing EE under additive or multiplicative relay-destination CSI errors. The optimal channel-diagonalizing structure is derived for the source covariance and relay beamforming matrices under the spectral-norm constrained additive or multiplicative CSI error. Then the existence of a saddle point is proved, which shows that the channel-diagonalizing transmission strategy is optimal in the robust EE maximization under these two types of CSI errors, and the original matrix-valued fractional robust EE problem is transformed into a scalar fractional problem. We propose the Dinkelbach method based alternating optimization scheme for this transformed robust EE problem, which is capable of finding a locally optimal solution of the original robust EE problem efficiently, and show that the semi-closed-form solution to each of the two associated subproblems can be obtained. We then prove that the channel-diagonalizing transmission strategy remains optimal when the statistically imperfect source-relay channel is additionally imposed. We also extend our work into multi-hop MIMO relaying scenarios, and prove that the channeldiagonalizing structure is optimal for the source covariance matrix and multiple relay beamforming matrices.
1536-1276
4326-4343
Gong, Shiqi
56c61a3c-ffb4-4f08-a817-9cd4d073c6ad
Wang, Shuai
f2fa510e-d1de-415f-84e4-0f143946243a
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Xing, Chengwen
2477f24d-3711-47b1-b6b4-80e2672a48d1
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Gong, Shiqi
56c61a3c-ffb4-4f08-a817-9cd4d073c6ad
Wang, Shuai
f2fa510e-d1de-415f-84e4-0f143946243a
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Xing, Chengwen
2477f24d-3711-47b1-b6b4-80e2672a48d1
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Gong, Shiqi, Wang, Shuai, Chen, Sheng, Xing, Chengwen and Hanzo, Lajos (2019) Robust energy efficiency optimization for amplify-and-forward MIMO relaying systems. IEEE Transactions on Wireless Communications, 18 (9), 4326-4343. (doi:10.1109/TWC.2019.2923200).

Record type: Article

Abstract

We investigate the energy efficiency (EE) of multiple-input multiple-output (MIMO) amplify-and-forward relaying networks relying on the realistic imperfect channel state information (CSI). Specifically, the relay jointly optimizes the source covariance and relay beamforming matrices by maximizing EE under additive or multiplicative relay-destination CSI errors. The optimal channel-diagonalizing structure is derived for the source covariance and relay beamforming matrices under the spectral-norm constrained additive or multiplicative CSI error. Then the existence of a saddle point is proved, which shows that the channel-diagonalizing transmission strategy is optimal in the robust EE maximization under these two types of CSI errors, and the original matrix-valued fractional robust EE problem is transformed into a scalar fractional problem. We propose the Dinkelbach method based alternating optimization scheme for this transformed robust EE problem, which is capable of finding a locally optimal solution of the original robust EE problem efficiently, and show that the semi-closed-form solution to each of the two associated subproblems can be obtained. We then prove that the channel-diagonalizing transmission strategy remains optimal when the statistically imperfect source-relay channel is additionally imposed. We also extend our work into multi-hop MIMO relaying scenarios, and prove that the channeldiagonalizing structure is optimal for the source covariance matrix and multiple relay beamforming matrices.

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Accepted/In Press date: 5 June 2019
e-pub ahead of print date: 24 June 2019
Published date: September 2019

Identifiers

Local EPrints ID: 431809
URI: http://eprints.soton.ac.uk/id/eprint/431809
ISSN: 1536-1276
PURE UUID: 6cc901f6-2c91-4cb8-ad26-25dd54497c87
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 18 Jun 2019 16:30
Last modified: 07 Oct 2020 01:33

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