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Register a new userPhysical Layer Security of Intelligent Reflective Surface Aided NOMA Networks
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Added by
Zhiqing Tang
Publication date
2020
fields
Electronic Engineering
and research's language is
English
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Intelligent reflective surface (IRS) technology is emerging as a promising performance enhancement technique for next-generation wireless networks. Hence, we investigate the physical layer security of the downlink in IRS-aided non-orthogonal multiple access networks in the presence of an eavesdropper, where an IRS is deployed for enhancing the quality by assisting the cell-edge user to communicate with the base station. To characterize the networks performance, the expected value of the new channel statistics is derived for the reflected links in the case of Nakagami-m fading. Furthermore, the performance of the proposed network is evaluated both in terms of the secrecy outage probability (SOP) and the average secrecy capacity (ASC). The closed-form expressions of the SOP and the ASC are derived. We also study the impact of various network parameters on the overall performance of the network considered. To obtain further insights, the secrecy diversity orders and the high signal-to-noise ratio slopes are obtained. We finally show that: 1) the expectation of the channel gain in the reflected links is determined both by the number of IRSs and by the Nakagami-m fading parameters; 2) The SOP of both receiver 1 and receiver 2 becomes unity, when the number of IRSs is sufficiently high; 3) The secrecy diversity orders are affected both by the number of IRSs and by the Nakagami-m fading parameters, whereas the high-SNR slopes are not affected by these parameters. Our Monte-Carlo simulations perfectly demonstrate the analytical results.
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The intrinsic integration of the nonorthogonal multiple access (NOMA) and reconfigurable intelligent surface (RIS) techniques is envisioned to be a promising approach to significantly improve both the spectrum efficiency and energy efficiency for future wireless communication networks. In this paper, the physical layer security (PLS) for a RIS-aided NOMA 6G networks is investigated, in which a RIS is deployed to assist the two dead zone NOMA users and both internal and external eavesdropping are considered. For the scenario with only internal eavesdropping, we consider the worst case that the near-end user is untrusted and may try to intercept the information of far-end user. A joint beamforming and power allocation sub-optimal scheme is proposed to improve the system PLS. Then we extend our work to a scenario with both internal and external eavesdropping. Two sub-scenarios are considered in this scenario: one is the sub-scenario without channel state information (CSI) of eavesdroppers, and another is the sub-scenario where the eavesdroppers CSI are available. For the both sub-scenarios, a noise beamforming scheme is introduced to be against the external eavesdroppers. An optimal power allocation scheme is proposed to further improve the system physical security for the second sub-scenario. Simulation results show the superior performance of the proposed schemes. Moreover, it has also been shown that increasing the number of reflecting elements can bring more gain in secrecy performance than that of the transmit antennas.
In this paper, we investigate a large intelligent surface-enhanced (LIS-enhanced) system, where a LIS is deployed to assist secure transmission. Our design aims to maximize the achievable secrecy rates in different channel models, i.e., Rician fading and (or) independent and identically distributed Gaussian fading for the legitimate and eavesdropper channels. In addition, we take into consideration an artificial noise-aided transmission structure for further improving system performance. The difficulties of tackling the aforementioned problems are the structure of the expected secrecy rate expressions and the non-convex phase shift constraint. To facilitate the design, we propose two frameworks, namely the sample average approximation based (SAA-based) algorithm and the hybrid stochastic projected gradient-convergent policy (hybrid SPG-CP) algorithm, to calculate the expectation terms in the secrecy rate expressions. Meanwhile, majorization minimization (MM) is adopted to address the non-convexity of the phase shift constraint. In addition, we give some analyses on two special scenarios by making full use of the expectation terms. Simulation results show that the proposed algorithms effectively optimize the secrecy communication rate for the considered setup, and the LIS-enhanced system greatly improves secrecy performance compared to conventional architectures without LIS.
This paper proposes a novel framework of resource allocation in intelligent reflecting surface (IRS) aided multi-cell non-orthogonal multiple access (NOMA) networks, where a sum-rate maximization problem is formulated. To address this challenging mixed-integer non-linear problem, we decompose it into an optimization problem (P1) with continuous variables and a matching problem (P2) with integer variables. For the non-convex optimization problem (P1), iterative algorithms are proposed for allocating transmit power, designing reflection matrix, and determining decoding order by invoking relaxation methods such as convex upper bound substitution, successive convex approximation and semidefinite relaxation. For the combinational problem (P2), swap matching-based algorithms are proposed to achieve a two-sided exchange-stable state among users, BSs and subchannels. Numerical results are provided for demonstrating that the sum-rate of the NOMA networks is capable of being enhanced with the aid of the IRS.
Reconfigurable intelligent surface (RIS), a recently introduced technology for future wireless com-munication systems, enhances the spectral and energy efficiency by intelligently adjusting the propaga-tion conditions between a base station (BS) and mobile equipments (MEs). An RIS consists of manylow-cost passive reflecting elements to improve the quality of the received signal. In this paper, westudy the problem of power control at the BS for the RIS aided physical-layer broadcasting. Our goalis to minimize the transmit power at the BS by jointly designing the transmit beamforming at the BSand the phase shifts of the passive elements at the RIS. Furthermore, to help validate the proposedoptimization methods, we derive lower bounds to quantify the average transmit power at the BS as afunction of the number of MEs, the number of RIS elements, and the number of antennas at the BS.The simulation results demonstrated that the average transmit power at the BS is close to the lowerbound in an RIS aided system, and is significantly lower than the average transmit power in conventionalschemes without the RIS.
In this paper, we introduce an intelligent reflecting surface (IRS) to provide a programmable wireless environment for physical layer security. By adjusting the reflecting coefficients, the IRS can change the attenuation and scattering of the incident electromagnetic wave so that it can propagate in a desired way toward the intended receiver. Specifically, we consider a downlink multiple-input single-output (MISO) broadcast system where the base station (BS) transmits independent data streams to multiple legitimate receivers and keeps them secret from multiple eavesdroppers. By jointly optimizing the beamformers at the BS and reflecting coefficients at the IRS, we formulate a minimum-secrecy-rate maximization problem under various practical constraints on the reflecting coefficients. The constraints capture the scenarios of both continuous and discrete reflecting coefficients of the reflecting elements. Due to the non-convexity of the formulated problem, we propose an efficient algorithm based on the alternating optimization and the path-following algorithm to solve it in an iterative manner. Besides, we show that the proposed algorithm can converge to a local (global) optimum. Furthermore, we develop two suboptimal algorithms with some forms of closed-form solutions to reduce the computational complexity. Finally, the simulation results validate the advantages of the introduced IRS and the effectiveness of the proposed algorithms
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