Transmit antenna selection and beamformer design for secure spatial modulation with rough CSI for Eve
Transmit antenna selection and beamformer design for secure spatial modulation with rough CSI for Eve
The security of spatial modulation (SM) aided net-works can always be improved by reducing the desired link’s power at the cost of degrading its bit error ratio performance and assuming the power consumed to artificial noise (AN) projection (ANP). We formulate the joint optimization problem of maximizing the secrecy rate (Max-SR) over the transmit antenna selection and ANP in the context of secure SM-aided networks. In order to solve this problem, we provide a pair of solutions, namely joint and separate solutions. Specifically, an accurate approximation of the SR is used for reducing the computational complexity, and the optimal AN covariance matrix (ANCM) is found by convex optimization for any given active antenna group (AAG). Then, given a large set of AAGs, simulated annealing mechanism is invoked for optimizing the choice of AAG, where the corresponding ANCM is recomputed by this optimization method as well when the AAG changes. To further reduce the complexity of the above-mentioned joint optimization, a low-complexity two-stage separate optimization method is also proposed. Moreover, when the number of transmit antennas tends to infinity, the Max-SR problem becomes equivalent to that of maximizing the ratio of the desired user’s signal-to-interference-plus-noise ratio to the eavesdropper’s. Thus, our original problem reduces to a fractional programming problem and a significant computational complexity reduction can be achieved. Finally, our simulation results verify the efficiency of the proposed methods in terms of the SR performance attained.
active antenna group selection, artificial noise, finite-alphabet input, secure transmission, Spatial modulation
4643-4656
Xia, Guiyang
e9762ed1-aa8c-4e8a-aa4e-34728b0ffd8c
Lin, Yan
f3f15b46-e506-4e57-b35a-18daf97cdd8c
Liu, Tingting
43fdbe8d-9050-4b44-aae3-609976f3c823
Shu, Feng
862e7a4a-480e-440f-a2f9-6d31f6397930
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
1 July 2020
Xia, Guiyang
e9762ed1-aa8c-4e8a-aa4e-34728b0ffd8c
Lin, Yan
f3f15b46-e506-4e57-b35a-18daf97cdd8c
Liu, Tingting
43fdbe8d-9050-4b44-aae3-609976f3c823
Shu, Feng
862e7a4a-480e-440f-a2f9-6d31f6397930
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Xia, Guiyang, Lin, Yan, Liu, Tingting, Shu, Feng and Hanzo, Lajos
(2020)
Transmit antenna selection and beamformer design for secure spatial modulation with rough CSI for Eve.
IEEE Transactions on Wireless Communications, 19 (7), , [9064699].
(doi:10.1109/TWC.2020.2985968).
Abstract
The security of spatial modulation (SM) aided net-works can always be improved by reducing the desired link’s power at the cost of degrading its bit error ratio performance and assuming the power consumed to artificial noise (AN) projection (ANP). We formulate the joint optimization problem of maximizing the secrecy rate (Max-SR) over the transmit antenna selection and ANP in the context of secure SM-aided networks. In order to solve this problem, we provide a pair of solutions, namely joint and separate solutions. Specifically, an accurate approximation of the SR is used for reducing the computational complexity, and the optimal AN covariance matrix (ANCM) is found by convex optimization for any given active antenna group (AAG). Then, given a large set of AAGs, simulated annealing mechanism is invoked for optimizing the choice of AAG, where the corresponding ANCM is recomputed by this optimization method as well when the AAG changes. To further reduce the complexity of the above-mentioned joint optimization, a low-complexity two-stage separate optimization method is also proposed. Moreover, when the number of transmit antennas tends to infinity, the Max-SR problem becomes equivalent to that of maximizing the ratio of the desired user’s signal-to-interference-plus-noise ratio to the eavesdropper’s. Thus, our original problem reduces to a fractional programming problem and a significant computational complexity reduction can be achieved. Finally, our simulation results verify the efficiency of the proposed methods in terms of the SR performance attained.
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ASandANdesign1
- Accepted Manuscript
More information
Accepted/In Press date: 31 March 2020
e-pub ahead of print date: 13 April 2020
Published date: 1 July 2020
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Funding Information:
Manuscript received May 5, 2019; revised October 25, 2019 and December 25, 2019; accepted March 30, 2020. Date of publication April 13, 2020; date of current version July 10, 2020. The work of Yan Lin was supported in part by the Fundamental Research Funds for the Central Universities under Grant 30919011227, and in part by the Natural Science Foundation of Jiangsu Province under Grant BK20190454. The work of Tingting Liu was supported by the National Natural Science Foundation of China under Grant 61702258. The work of Feng Shu was supported by the National Natural Science Foundation of China under Grant 61771244. The work of Lajos Hanzo was supported in part by the Engineering and Physical Sciences Research Council of the Royal Society’s Global Challenges Research Fund Grant as well as of the European Research Council’s Advanced Fellow Grant QuantCom under Project EP/N004558/1, Project EP/P034284/1, Project EP/P034284/1, and Project EP/P003990/1 (COALESCE). The associate editor coordinating the review of this article and approving it for publication was S. Yang. (Corresponding authors: Feng Shu; Lajos Hanzo.) Guiyang Xia, Yan Lin, and Feng Shu are with the School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China (e-mail: xiaguiyang@njust.edu.cn; yanlin@njust.edu.cn; shufeng@njust.edu.cn).
Copyright © 2020, IEEE
Keywords:
active antenna group selection, artificial noise, finite-alphabet input, secure transmission, Spatial modulation
Identifiers
Local EPrints ID: 439190
URI: http://eprints.soton.ac.uk/id/eprint/439190
ISSN: 1536-1276
PURE UUID: aa550b26-a0a7-4356-9e52-563a824d3bf5
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Date deposited: 06 Apr 2020 16:36
Last modified: 18 Mar 2024 05:26
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Author:
Guiyang Xia
Author:
Yan Lin
Author:
Tingting Liu
Author:
Feng Shu
Author:
Lajos Hanzo
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