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Uplink Secure Receive Spatial Modulation Empowered by Intelligent Reflecting Surface.

Liu, C., Shi, Z., Lin, M., Yu, F., Zheng, T.-X., Zhang, J. and Lu, G., 2021. Uplink Secure Receive Spatial Modulation Empowered by Intelligent Reflecting Surface. IEEE Internet of Things Journal, 14 (8), 1-16.

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Abstract

With the emergence of the fifth generation (5G) era, the development of the Internet of Things (IoT) network has been accelerated with a new impetus, making it imperative to strive for a more reliable and efficient network environment. To accomplish this, we introduce and investigate a novel proposal for the intelligent reflecting surface (IRS) enabled uplink secure receive spatial modulation (SM), named IRS-USRSM, to resolve the security issues arising from the open wireless transmission environment in the 5G IoT network. In the IRS-USRSM scheme, we assume that the passive eavesdropper is directly connected to the uplink user and occasionally connected to the IRS. To achieve enhanced secrecy with finite alphabet inputs, a joint transmitter perturbation and IRS reflection design for physical layer security is proposed to guarantee secure and reliable transmission of IRS-USRSM. Specifically, two categories of IRSbased random phase compensation strategies, namely, random perturbation compensation and random path synthesize, along with maximum likelihood detection and suboptimal detection are proposed to meet the variant design requirements between achieved performance and system cost. Furthermore, in order to evaluate the performance limits of the IRS-USRSM, the closedform results of average bit error probabilities and discrete-input continuous-output memoryless channel capacities are derived using the method of moment generating function. Simulation results are presented to verify the correctness of our theoretical analyses, as well as to demonstrate the efficiency and superiority of the proposed IRS-USRSM scheme.

Item Type:Article
ISSN:2327-4662
Group:Faculty of Science & Technology
ID Code:40089
Deposited By: Symplectic RT2
Deposited On:01 Jul 2024 13:32
Last Modified:01 Jul 2024 13:32

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