Performance of Joint Symbol Level Precoding and RIS Phase Shift Design in the Finite Block Length Regime with Constellation Rotation

In this paper, we tackle the problem of joint symbol level precoding (SLP) and reconfigurable intelligent surface (RIS) phase shift design with constellation rotation in the finite block length regime. We aim to increase energy efficiency by minimizing the total transmit power while satisfying the quality of service constraints. The total power consumption can be significantly minimized through the exploitation of multiuser interference by symbol level precoding and by the intelligent manipulation of the propagation environment using reconfigurable intelligent surfaces. In addition, the constellation rotation per user contributes to energy efficiency by aligning the symbol phases of the users, thus improving the utilization of constructive interference. The formulated power minimization problem is non-convex and correspondingly difficult to solve directly. Hence, we employ an alternating optimization algorithm to tackle the joint optimization of SLP and RIS phase shift design. The optimal phase of each user's constellation rotation is obtained via an exhaustive search algorithm. Through Monte-Carlo simulation results, we demonstrate that the proposed solution yields substantial power minimization as compared to conventional SLP, zero forcing precoding with RIS as well as the benchmark schemes without RIS.Comment: 6 pages,4 figures. This paper has been accepted by IEEE International Symposium on Personal, Indoor and Mobile Radio Communication

Performance of Joint Symbol Level Precoding and RIS Phase Shift Design in the Finite Block Length Regime with Constellation Rotation

peer reviewedIn this paper, we tackle the problem of joint symbol level precoding (SLP) and reconfigurable intelligent surface (RIS) phase shift design with constellation rotation in the finite block length regime. We aim to increase energy efficiency by minimizing the total transmit power while satisfying the quality of service constraints. The total power consumption can be significantly minimized through the exploitation of multiuser interference by symbol level precoding and by the intelligent manipulation of the propagation environment using reconfigurable intelligent surfaces. In addition, the constellation rotation per user contributes to energy efficiency by aligning the symbol phases of the users, thus improving the utilization of constructive interference. The formulated power minimization problem is non-convex and correspondingly difficult to solve directly. Hence, we employ an alternating optimization algorithm to tackle the joint optimization of SLP and RIS phase shift design. The optimal phase of each user’s constellation rotation is obtained via an exhaustive search algorithm. Through Monte-Carlo simulation results, we demonstrate that the proposed solution yields substantial power minimization as compared to conventional SLP, zero forcing precoding with RIS as well as the benchmark schemes without RIS

Joint RIS-aided Precoding and Multislot Scheduling for Maximum User Admission in Smart Cities

peer reviewedReconfigurable intelligent surfaces (RISs) have emerged as a game-changing technology to improve wireless network performance by intelligently manipulating and customizing the physical propagation environment. Such capability is especially important for the application of smart cities as it increases wireless service offers and quality to end-users. In this paper, we aim to maximize the number of served users in a challenging RIS-aided smart city street by jointly optimizing the multislot scheduling, precoding, and passive RIS-based beamforming design under quality of service and power constraints. Multislot scheduling is introduced in order to benefit from additional time diversity and thus better exploit the available degrees of freedom. The formulated problem is a mixed integer nonlinear programming, which is NP-hard. To solve the problem with affordable complexity, we develop an efficient iterative algorithm based on binary variable relaxation, alternating optimization, and successive convex approximation techniques. Simulation results demonstrate the superiority of the proposed design over the design without RIS and the design without scheduling, especially in the presence of a large number of users. In addition, results illustrate that by introducing a quality of service margin, the proposed design can improve its robustness to outdated channel state information in mobility scenarios

Resource Allocation for Geographical Fairness in Multi-RIS-Aided Outdoor-to-Indoor Communications

peer reviewedIn this paper, we study the resource allocation problem in multi-RIS-aided outdoor-to-indoor communications. Specifically, we aim to provide geographical fairness to ensure that users in different hotspot areas in a smart city can be served regardless of their location. We consider a scenario where RISs are deployed to extend coverage to indoor users in different buildings where there is limited network accessibility. This design is crucial in smart cities in the context of emergency communication and ubiquitous connectivity since it ensures service availability to as many users as possible independently of the locations. Thus, to achieve geographical fairness, we formulate a max-min fairness problem to maximize the minimum number of users served by each RIS by jointly optimizing the active precoding and RIS-based beamforming subject to power and quality of service constraints. The geographical location of users is directly linked to the RIS which means that users are served by the RIS closest to them. In this case, we ensure that a certain number of users can be supported by each RIS. The formulated problem is a mixed integer non-linear program, which is challenging to solve directly using methods of convex optimization. Accordingly, we propose an efficient successive convex approximation-based alternating optimization algorithm to tackle the complexity of the formulated problem. The presented results show the performance gain of the proposed design in providing geographical fairness compared to the relevant benchmark schemes.U-AGR-7046 - C20/IS/14773976/RISOTTI - OTTERSTEN Björ