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IEEE Globecom Workshops (GC Wkshps)

Secrecy Outage-Constrained Robust Resource Allocation Design for MU-MISO RSMA Systems

Hao Fu, Suili Feng, Weijun Tang, Zhiqiang Wei, Derrick Wing Kwan Ng

Published Dec 1, 2021• 2 citations
Publisher

Abstract

In this paper, we study the robust and fair transmission design for a rate splitting multiple access (RSMA)-based multi-user multiple-input single-output (MU-MISO) probabilistic secrecy communication system, where the statistic distribution of estimation errors of eavesdropping channels is available at the transmitter. Our robust resource allocation design aims to maximize the minimum achievable outage constrained (OC) secrecy rate among multiple single-antenna legitimated users (LUs) via optimizing the beamforming vectors and the artificial noise (AN) matrix at the transmitter. To this end, the algorithm design is formulated as a non-convex probabilistic optimization problem which takes into account the maximum transmit power budget. To address the intractability of the optimization problem, the successive convex approximation (SCA) technique and the alternating optimization (AO) approach are exploited to design a suboptimal iterative algorithm for obtaining a locally optimal solution of the considered problem. Simulation results demonstrate that the minimum achievable OC secrecy rate performance of our proposed RSMA-based probabilistic secure transmission system outperforms that of several baseline schemes.

DOI
10.1109/gcwkshps52748.2021.9682157

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In this paper, we study the robust and fair transmission design for a rate splitting multiple access (RSMA)-based multi-user multiple-input single-output (MU-MISO) probabilistic secrecy communication system, where the statistic distribution of estimation errors of eavesdropping channels is available at the transmitter. Our robust resource allocation design aims to maximize the minimum achievable outage constrained (OC) secrecy rate among multiple single-antenna legitimated users (LUs) via optimizing the beamforming vectors and the artificial noise (AN) matrix at the transmitter. To this end, the algorithm design is formulated as a non-convex probabilistic optimization problem which takes into account the maximum transmit power budget. To address the intractability of the optimization problem, the successive convex approximation (SCA) technique and the alternating optimization (AO) approach are exploited to design a suboptimal iterative algorithm for obtaining a locally optimal solution of the considered problem. Simulation results demonstrate that the minimum achievable OC secrecy rate performance of our proposed RSMA-based probabilistic secure transmission system outperforms that of several baseline schemes.
In this paper, we consider max-min fairness for a downlink two-user multi-input single-output (MISO) system with imperfect channel state information available at transmitter (CSIT) taking into account the total power constraint and the physical layer security. To handle the worst-case channel uncertainty of a potential eavesdropper (PE), we study the robust secure resource allocation algorithm which maximizes the minimum achieved worst-case secrecy rate among single-antenna legitimate users. In contrast to existing schemes adopted in the literature, we propose a rate-splitting (RS)-based secure transmission scheme, which advocates the dual use of a common message serving both as a desired message and artificial noise (AN) for legitimate users and the PE, respectively. Considering the non-convex resource allocation algorithm design problem, we apply the majorization maximization (MM) method to obtain a suboptimal iterative algorithm. In each iteration, a rank-constrained semi-definite program (SDP) is solved optimally by SDP relaxation (SDR). Simulation results demonstrate that our proposed robust secure beamforming scheme in the MISO-RS secure transmission system outperforms that of several baselines.
In this paper, we consider max-min fairness for a downlink two-user multi-input single-output (MISO) system with imperfect channel state information available at transmitter (CSIT) taking into account the total power constraint and the physical layer security. Considering the worst-case channel uncertainty for a potential eavesdropper (PE), we study the robust secure beamforming algorithm design which maximizes the minimum achieved worst-case secrecy rate among single-antenna legitimate users. In contrast to existing schemes adopted in the literatures, we propose a rather unorthodox rate splitting (RS) scheme which advocates the dual use of a common message serving both as a desired message and artificial noise (AN) for legitimate users and the PE, respectively. The algorithm design is formulated as a non-convex optimization problem which is generally intractable. As a compromise approach, we apply the successive convex approximation (SCA) method which facilitates the design of a low-complexity suboptimal iterative algorithm. In each iteration, a rank-constrained semi-definite program (SDP) is solved optimally by SDP relaxation (SDR). Simulation results demonstrate that our proposed robust secure beamforming scheme in the MISO-RS secure transmission system outperforms that of the non-robust counterpart. Moreover, our results also unveil that the proposed RS scheme can achieve a superior performance compared to the existing non-orthogonal multiple access (NOMA) schemes and the traditional scheme.
This letter exploits secure beamforming for achieving security-reliability tradeoff in rate splitting multiple access (RSMA)-based communications against eavesdropper collusion. Considering user fairness, we maximize the minimum secrecy rate (MSR) among all legitimate users subject to the quality of service (QoS) constraints and transmit power constraint. A feasibility check problem is first presented to avoid infeasible cases. Then, a successive convex approximation-based algorithm is proposed to iteratively optimize the beamforming design. Numerical results show that the proposed RSMA-based design outperforms the baseline design in terms of MSR within certain QoS requirement ranges to trade security for reliability by balancing the power allocated to the common stream and private streams. And the performance advantage enlarges as the number of collusive eavesdroppers increases.
Rate splitting multiple access (RSMA) is promising to achieve high spectral efficiency with a higher flexibility relative to non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA). In this paper, a novel RSMA-based secure transmission scheme with artificial noise (AN) and an adaptive beamforming is developed with the aim of maximizing the secrecy sum rate (SSR) of the considered system subject to specific constraints. The joint optimization of the power allocation between useful messages and AN signals, rate splitting between the two legitimate receivers, and the two mastering parameters of the beamforming design is tackled. To solve such a non-convex problem, we first analytically reveal some properties of the solution and then focus on an asymptotic scenario with a sufficiently large number of transmit antennas to derive closed-form expressions for the optimal power allocation coefficients. This enables us to develop an efficient method to identify the optimal rate splitting and beamforming parameters. Our examinations demonstrate that the proposed RSMA-based scheme outperforms two benchmark schemes in terms of achieving a higher SSR and the achievable performance gain is exceptional when the number of transmit antennas is small.
This paper addresses robust designs of secure simultaneous wireless information and power transfer for multiple-input single-output (MISO) multiuser systems. By using a bounded uncertainty model for the channel state information (CSI) from transmitters to legitimate receivers and under the assumption of only available statistic knowledge of the CSI to eavesdroppers, we consider the robust designs with both worst-case and chance-constrained optimizations. To jointly optimize transmit beamforming vectors and power splitting factors, we formulate three problems aiming at minimizing the system power, maximizing the sum secrecy rate, and maximizing the minimal secrecy rate, respectively, subject to both energy harvesting and secrecy outage constraints. These problems are intractable in their original forms due to the CSI models and their non-convexity. To reach computationally efficient solutions, we first rewrite the original problems by semi-definite relaxation, then transform the CSI uncertainty related constraints by S-procedure, and finally approximate the non-convex constraints by the first-order Taylor expansion. By the reformulations, we present iterative successive convex approximation algorithm for approaching the optimized solutions. Simulation results under various setups of system parameters are provided to examine the system performance and validate the effectiveness of the proposed schemes.
In this letter, we investigate the simultaneous wireless information and power transfer in a multiple-input-single-output downlink system which consists of one multi-antenna transmitter, one single-antenna desired receiver, and multiple single-antenna eavesdroppers. Specifically, we investigate the outage-constrained secrecy rate maximization by jointly designing the transmit beamforming vector and the power splitting ratio with statistical channel uncertainties. To handle the formulated non-convex problem, we resort to semi-definite relaxation (SDR) and the Bernstein-type inequality to transform the outage constraints into a deterministic form. Then, the original problem can be efficiently solved by alternately optimizing two convex subproblems. In addition, we testify that the SDR can obtain the rank-one optimal solution. Finally, our proposed algorithm is validated by some representative numerical results.