Robust beamforming for multibeam satellite communication in the face of phase perturbations
Robust beamforming for multibeam satellite communication in the face of phase perturbations
A precoding scheme is proposed for the downlink of multibeam satellite communication in the face of phase perturbations. In order to alleviate the signal-to-interference and noise ratio (SINR) degradation induced by phase uncertainty and to minimize the transmission power consumption, we formulated the beamforming problem as a chance-constrained optimization. Moreover, we provided a large deviation inequality (LDI) aided conservative approximation for the chance-constraints, followed by conceiving a tractable solution. Our simulation results showed the accuracy and the efficiency of our proposed approximation algorithm compared to the benchmarks.
Zhang, Xin
788d80a9-6117-4670-81ef-f8ef2d26d30c
Wang, Jingjing
a394f598-6ec0-4da3-bfbc-7e13fce9282b
Jiang, Chunxiao
16bad068-43b1-41d4-9f6b-211acdb1ae52
Yan, Chaoxing
c7bc0d86-7445-4705-a830-2041c52d9b79
Ren, Yong
ad146a10-75d8-401c-911b-fd4dcc44eb12
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhang, Xin
788d80a9-6117-4670-81ef-f8ef2d26d30c
Wang, Jingjing
a394f598-6ec0-4da3-bfbc-7e13fce9282b
Jiang, Chunxiao
16bad068-43b1-41d4-9f6b-211acdb1ae52
Yan, Chaoxing
c7bc0d86-7445-4705-a830-2041c52d9b79
Ren, Yong
ad146a10-75d8-401c-911b-fd4dcc44eb12
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhang, Xin, Wang, Jingjing, Jiang, Chunxiao, Yan, Chaoxing, Ren, Yong and Hanzo, Lajos
(2019)
Robust beamforming for multibeam satellite communication in the face of phase perturbations.
IEEE Transactions on Vehicular Technology.
(doi:10.1109/TVT.2019.2896245).
Abstract
A precoding scheme is proposed for the downlink of multibeam satellite communication in the face of phase perturbations. In order to alleviate the signal-to-interference and noise ratio (SINR) degradation induced by phase uncertainty and to minimize the transmission power consumption, we formulated the beamforming problem as a chance-constrained optimization. Moreover, we provided a large deviation inequality (LDI) aided conservative approximation for the chance-constraints, followed by conceiving a tractable solution. Our simulation results showed the accuracy and the efficiency of our proposed approximation algorithm compared to the benchmarks.
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Accepted/In Press date: 24 January 2019
e-pub ahead of print date: 30 January 2019
Identifiers
Local EPrints ID: 427999
URI: http://eprints.soton.ac.uk/id/eprint/427999
ISSN: 0018-9545
PURE UUID: 65ca162d-2510-48e6-991f-b340f62cef00
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Date deposited: 06 Feb 2019 17:30
Last modified: 18 Mar 2024 02:36
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Contributors
Author:
Xin Zhang
Author:
Jingjing Wang
Author:
Chunxiao Jiang
Author:
Chaoxing Yan
Author:
Yong Ren
Author:
Lajos Hanzo
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