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In this letter, a underlay cognitive radio inspired non-orthogonal multiple access (CR-NOMA) network assisted by the reconfigurable intelligent surface (RIS) technique is conceived to maximize the energy efficiency (EE), while all the cognitive users (CUs) are located in the “dead zone”. In particular, the CUs could only receive the information from the cognitive base station (CBS) via RIS. The EE maximization optimization problem which is a non-convex problem has been constructed to realize joint beamforming design at both the CBS and RIS with the constraints of the primary user’s (PU) interference power restriction and the CUs’ rate fairness. Moreover, we propose the alternating pragmatic iterative algorithm (APIA) to optimize the non-convex optimization problem until the final value of EE converges. Based on the simulation results, our proposed algorithm attains the significant gain than the two benchmarks of the random phase scheme as well as the fixed phase scheme on the RIS. [ABSTRACT FROM AUTHOR]

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 network's 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 (SNR) 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 IRS elements and by the Nakagami- $m$ fading parameters; 2) If the Nakagami- $m$ parameter is no less than 2, the SOP of both User 1 and User 2 becomes unity, when the number of IRS elements tends to infinity; 3) The secrecy diversity orders are affected both by the number of IRS elements 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. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the downlink secure beamforming (BF) design problem of cloud radio access networks (C-RANs) relying on multicast fronthaul, where millimeter-wave and microwave carriers are used for the access links and fronthaul links, respectively. The base stations (BSs) jointly serve users through cooperating hybrid analog/digital BF. We first develop an analog BF for cooperating BSs. On this basis, we formulate a secrecy rate maximization (SRM) problem subject both to a realistic limited fronthaul capacity and to the total BS transmit power constraint. Due to the intractability of the non-convex problem formulated, advanced convex approximated techniques, constrained concave convex procedures and semi-definite programming (SDP) relaxation are applied to transform it into a convex one. Subsequently, an iterative algorithm of jointly optimizing multicast BF, cooperative digital BF and the artificial noise (AN) covariance is proposed. Next, we construct the solution of the original problem by exploiting both the primal and the dual optimal solution of the SDP-relaxed problem. Furthermore, a per-BS transmit power constraint is considered, necessitating the reformulation of the SRM problem, which can be solved by an efficient iterative algorithm. We then eliminate the idealized simplifying assumption of having perfect channel state information (CSI) for the eavesdropper links and invoke realistic imperfect CSI. Furthermore, a worst-case SRM problem is investigated. Finally, by combining the so-called $\mathcal {S}$ -Procedure and convex approximated techniques, we design an efficient iterative algorithm to solve it. Simulation results are presented to evaluate the secrecy rate and demonstrate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]