Intelligent reflecting surface (IRS) is capable of constructing the favorable wireless propagation environment by leveraging massive low-cost reconfigurable reflectarray elements. In this paper, we investigate the IRS-aided MIMO simultaneous wireless information and power transfer (SWIPT) for Internet of Things (IoT) networks, where the active base station (BS) transmit beamforming and the passive IRS reflection coefficients are jointly optimized for maximizing the minimum signal-to-interference-plus-noise ratio (SINR) among all information decoders (IDs), while maintaining the minimum total harvested energy at all energy receivers (ERs). Moreover, the IRS with practical discrete phase shifts is considered, and thereby the max-min SINR problem becomes a NP-hard combinatorial optimization problem with a strong coupling among optimization variables. To explore the insights and generality of this max-min design, both the Single-ID Single-ER (SISE) scenario and the Multiple-IDs Multiple-ERs (MIME) scenario are studied. In the SISE scenario, the classical combinatorial optimization techniques, namely the special ordered set of type 1 (SOS1) and the reformulation-linearization (RL) technique, are applied to overcome the difficulty of this max-min design imposed by discrete optimization variables. Then the optimal branch-and-bound algorithm and suboptimal alternating optimization algorithm are respectively proposed. We further extend the idea of alternating optimization to the MIME scenario. Moreover, to reduce the iteration complexity, a two-stage scheme is considered aiming to separately optimize the BS transmit beamforming and the IRS reflection coefficients. Finally, numerical simulations demonstrate the superior performance of the proposed algorithms over the benchmarks in both the two scenarios.

With the development of the sixth-generation wireless communication technology, the difficulty of covert communication in the satellite communications system (SCS) is further increased. In this article, a satellite covert communication system based on reconfigurable intelligent surface (RIS) is studied, which consists of a satellite, a terrestrial receiver, RIS, and a warden. Specifically, the ground terminal simultaneously receives the signal transmitted by the satellite and the signal reflected by RIS, while the warden wants to overhear the transmitted signal from the satellite and that reflected by the RIS. The main target of this wort is to maximize the minimum covert rate to improve signal quality while considering the limited onboard resources, the hardware constraints of RIS, and the requirement to implement covert communication. To address the nonconvex problem, we propose an effective alternating optimization scheme by jointly optimizing transmitter precoding and RIS to improve the covert communication performance of the considered system. In addition to ideal RIS, we also consider the nonideal RIS, the angle of which is discrete in the actual case. In addition, several simplified methods are proposed to decrease the computational complexity of the covert communication optimal problem under multiple terminals. Finally, simulation results are provided to verify the superiority of the proposed scheme compared with the benchmark scheme, which suggests that the considered RIS-based satellite–terrestrial covert communication system can significantly improve the achievable masking.

The use of simultaneous wireless information and power transfer (SWIPT) is a key enabler of achieving convenience and prolonging the energy supply lifetime of wireless networks. To address the low efficiencies of far-field power transfer, a reconfigurable intelligent surface (RIS) is adopted to enhance the energy harvesting (EH) performance, which can construct a favorable wireless propagation environment. In this paper, we consider an RIS-assisted SWIPT system with wireless transfer from the access point (AP) to multiple-antenna receivers, which include information receivers (IRs) and energy receivers (ERs). First, we formulate the problem of maximizing the minimum rates of the IRs as a nonconvex constrained optimization problem. For ideal and nonideal channels, we propose two different solutions. Second, we simplify the objective function and decompose the problem into several subproblems by using sorting and iterative optimization algorithms. Moreover, under optimal boundary and Karush-Kuhn-Tucker (KKT) conditions, we successfully solve this problem. The simulation results illustrate a promising approach for wireless communication by comparing ideal RIS and unsatisfactory situations with no RIS cases under various conditions.

With the rapidly increasing demands for wireless communication networks, unmanned aerial vehicles (UAVs) have been developed. However, the line-of-sight (LoS) links are susceptible to severe deterioration due to complex distribution environments. To tackle this issue, Reconfigurable Intelligent Surface (RIS) technology has been introduced to ameliorate the propagation environment and enhance communication performance. This paper explores a RIS-assisted simultaneous wireless information and power transfer (SWIPT) system to investigate the optimization problem involving UAV trajectory design, precoding, and RIS phase shift. The objective is to maximize the minimum information receivers' (IRs) rate. Considering that the problem is nonconvex, we decompose it into three subproblems and then solve it using an alternating optimization algorithm and the successive convex approximation (SCA) technique. Additionally, the paper takes into account the phase dispersion of the UAV no-fly zone and RIS, based on the actual situation. To address these non-ideal factors, we introduce an indicator function flag and employ the Dinkelbach method to obtain the optimal solution for the non-ideal optimization problem. The numerical results demonstrate that the proposed algorithm considerably improves the rate performance of the system.

Hybrid energy supply composed of batteries and radio frequency (RF) signals has been anticipated to be a prominent solution for balancing the reliability and self-sustainability of future IoT networks. The newly emerging reconfigurable intelligent surface (RIS) is also capable of greatly enhancing spectral and energy efficiencies. In this paper, by considering an asynchronous transmission protocol among all energy receivers (ERs) and assuming the perfect self-interference cancellation (SIC) at the hybrid access point (HAP), we aim to maximize sum throughput in the RIS-aided hybrid powered communication networks (HPCNs) by jointly optimizing the transmit covariance matrices of the HAP and all ERs, the RIS reflection matrix and the downlink/uplink (DL/UL) time allocation. Generally, this optimization problem is intractable to solve due to strongly coupled variables and nonconvex unit-modulus constraints. To draw more insights into this joint design, we firstly carry out feasibility analysis on this problem, and then develop a 2-block alternating optimization algorithm, which consists of the semi-closed-form solution based iterative algorithm for deriving the optimal MIMO transceivers together with the DL/UL time allocation and the alternating direction method of multipliers (ADMM) based algorithm for the RIS design. To avoid the potential high complexity of alternating optimization, we also propose a two-stage scheme, where the RIS design is independent of the others and aims to create favorable DL/UL channels. The extension of our proposed algorithms to the practical imperfect SIC case is then discussed. Numerical results illustrate the superior performance of our proposed algorithms over the baselines in terms of the achievable sum throughput, and their time effectiveness in solving large-scale problems.

In light of the growing necessity for secure satellite communications, harmful interference in channel transmission needs to be considered. By introducing Reconfigurable Intelligent Surfaces (RIS) into the wireless communication system, this paper presents a satellite-to-ground transmission system to mitigate harmful interference caused by unmanned aerial vehicle (UAV). We focus on downlink transmissions from satellites to users, examining both single-user and multi-user scenarios in the presence of multiple eavesdroppers (EVEs). This paper aims to maximize the achievable secrecy rate while adhering to the power constraints of the RIS and satellite transmitter, a nonconvex problem. To solve this problem, this paper employs several methods to the traditional alternating optimization (AO) algorithm to get an integrated advanced techniques method, which includes the LogSumExp function, genetic algorithms (GAs), Lagrange multipliers, derivation, and the branch-and-bound method and KKT conditions. The proposed framework encompasses ideal active and passive RIS configurations for single-user scenarios and practical continuously adjustable phase RIS and discrete phase RIS for multi-user scenarios. The efficacy of the proposed approach is validated through comprehensive simulations, which demonstrate significant performance improvements over baseline scenarios that lack RIS or employ random phase methods.