Reconfigurable intelligent surface (RIS) has been viewed as a promising solution in constructing reconfigurable radio environment of the propagation channel and boosting the received signal power by smartly coordinating the passive elements’ phase shifts at the RIS. Inspired by this emerging technique, this article focuses on joint beamforming design and optimization for RIS-aided hybrid satellite-terrestrial relay networks, where the links from the satellite and base station (BS) to multiple users are blocked. Specifically, a refracting RIS cooperates with a BS, where the latter operates as a half-duplex decode-and-forward relay, in order to strengthen the desired satellite signals at the blocked users. Considering the limited onboard power resource, the design objective is to minimize the total transmit power of both the satellite and BS while guaranteeing the rate requirements of users. Since the optimized beamforming weight vectors at the satellite and BS, and phase shifters at the RIS are coupled, leading to a mathematically intractable optimization problem, we propose an alternating optimization scheme by utilizing singular value decomposition and uplink–downlink duality to optimize beamforming weight vectors, and using Taylor expansion and penalty function methods to optimize phase shifters iteratively. Finally, simulation results are provided to verify the superiority of the proposed scheme compared to the benchmark schemes.

Motivated by the fact that both security and energy efficiency are the fundamental requirements and design targets of future satellite communications, this letter investigates secure energy efficient beamforming in multibeam satellite systems, where the satellite user in each beam is surrounded by an eavesdropper attempting to intercept the confidential information. To simultaneously improve the transmission security and reduce power consumption, our design objective is to maximize the system secrecy energy efficiency (SEE) under the constraint of total transmit power budget. Different from the existing schemes with high complexity, we propose an alternating optimization scheme to address the SEE problem by decomposing the original nonconvex problem into subproblems. Specifically, we first utilize the signal-to-leakage-plus-noise ratio (SLNR) metric to obtain closed-form normalized beamforming weight vectors, while the successive convex approximation (SCA) method is used to efficiently solve the power allocation subproblem. Then, an iterative algorithm is proposed to obtain the suboptimal solutions. Finally, simulation results are provided to verify the superiority of the proposed scheme compared to the benchmark schemes.

This work exploits the potential of a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) in improving the security in a multiple-input single-output (MISO) network, where three transmission protocols, namely, energy splitting (ES), mode selection (MS), and time splitting (TS), are studied. The objective is to maximize the weighted sum secrecy rate (WSSR) by jointly designing the beamforming (BF) and the transmitting and reflecting coefficients (TARCs). A path-following based technique is first developed to covert the non-convex problem and design the BF and the TARCs in an alternating manner. Then, for the ES scheme, the TARCs are solved by a penalty concave convex procedure (PCCP) method. Besides, the proposed method is extended to the MS by solving a mixed-integer problem. While for the TS scheme, a two-layer optimization method is proposed. Finally, the simulation results validate the superiority of STAR-RIS.

With the increasing demand of high data rate and massive access in both ultra-dense and industrial Internet-of-things networks, spectral efficiency (SE) and energy efficiency (EE) are regarded as two important and inter-related performance metrics for future networks. In this paper, we investigate a novel integration of rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) into cellular systems to achieve a desirable tradeoff between SE and EE. Different from the commonly used passive RIS, we adopt reflection elements with active load to improve a newly defined metric, called resource efficiency (RE), which is capable of striking a balance between SE and EE. This paper focuses on the RE optimization by jointly designing the base station (BS) transmit precoding and RIS beamforming (BF) while guaranteeing the transmit and forward power budgets of the BS and RIS, respectively. To efficiently tackle the challenges for solving the RE maximization problem due to its fractional objective function, coupled optimization variables, and discrete coefficient constraint, the formulated nonconvex problem is solved by proposing a two-stage optimization framework. For the outer stage problem, a quadratic transformation is used to recast the fractional objective into a linear form, and a closed-form solution is obtained by using auxiliary variables. For the inner stage problem, the system sum rate is approximated into a linear function. Then, an alternating optimization (AO) algorithm is proposed to optimize the BS precoding and RIS BF iteratively, by utilizing the penalty dual decomposition (PDD) method. Simulation results demonstrate the superiority of the proposed design compared to other benchmarks.

In this work, we study a simultaneous transmitting and reflecting reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output network. For the system under consideration, we maximize the weighted sum rate, mainly based on the energy splitting (ES) scheme. To tackle this optimization problem, a sub-optimal block coordinate descent (BCD) algorithm is proposed to design the precoding matrices and the transmitting and reflecting coefficients (TRCs) in an alternate manner. Specifically, the precoding matrices are solved using the Lagrange dual method, while the TRCs are obtained using the constrained concave-convex procedure (CCCP). The simulation results reveal that: 1) Simultaneous transmitting and reflecting RIS (STAR-RIS) can achieve better performance than conventional reflecting/transmiting-only RIS; 2) In unicast communication, time switching (TS) scheme outperforms the ES and mode selection (MS) schemes, while in broadcast communication, ES scheme outperforms the TS and MS schemes.

This paper aims to investigate the benefit of using intelligent reflecting surface (IRS) in multi-user multiple-input single-output (MU-MISO) systems, in the presence of eavesdroppers. We maximize the weighted sum secrecy rate by jointly designing the secure beamforming (BF), the artificial noise (AN), as well as the phase shift of the IRS. An alternating optimization (AO) method is proposed to deal with the formulated non convex problem. In particular, the secure beamforming and AN jamming matrix are optimally designed via the successive convex approximation (SCA) approach for given phase shift, which can be derived by considering the alternating direction method of multiplier (ADMM) and element-wise block coordinate decent (EBCD) methods. Finally, simulation results are presented to show the benefit of the IRS in terms of improving the secrecy performance, when compared to other methods.