Efficient Design for Multi-user Downlink Beamforming with Reconfigurable Intelligent Surface

2023-12-31

AI Summary

This paper addresses the high-complexity power minimization problem for joint base station (BS) and reconfigurable intelligent surface (RIS) beamforming in RIS-aided downlink multi-group multicast systems. To tackle this, we propose the Alternating Multicast Beamforming (AMBF) algorithm. Our key contribution lies in the natural decoupling of the joint optimization into two subproblems: a BS-side multicast quality-of-service (QoS) problem and an RIS-side passive multicast max-min fairness (MMF) problem. For the latter, we design a semi-closed-form solver based on the projected subgradient algorithm (PSA), achieving linear time complexity. Overall, AMBF’s computational complexity scales linearly with both the number of RIS elements and BS antennas. Under guaranteed user QoS constraints, AMBF significantly reduces both transmit power and computational overhead, outperforming state-of-the-art methods in both performance and efficiency.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Mechanism Design

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

This paper considers downlink multi-user transmission facilitated by a reconfigurable intelligent surface (RIS). First, focusing on the multi-group multicast beamforming scenario, we develop a fast and scalable algorithm for the joint base station (BS) and RIS beamforming optimization to minimize the transmit power subject to the user quality-of-service (QoS) constraints. By exploring the structure of this QoS problem, we show that the joint beamforming optimization can be naturally decomposed into a BS multicast beamforming QoS problem and an RIS passive multicast beamforming max-min-fair (MMF) problem. We propose an alternating multicast beamforming (AMBF) algorithm to solve the two subproblems alternatingly. For the BS QoS subproblem, we utilize the optimal multicast beamforming structure to obtain the BS beamformers efficiently. Furthermore, we reformulate the challenging RIS MMF subproblem and employ a first-order projected subgradient algorithm (PSA), which yields closed-form updates. The computational complexity of the AMBF algorithm grows linearly with the number of RIS elements and BS antennas. We further show that the AMBF approach is also an efficient method for the RIS-assisted downlink multi-user unicast beamforming problem, providing semi-closed-form updates. Next, we study the MMF problem for the RIS-assisted downlink beamforming design and propose a PSA-based fast algorithm to compute the BS and RIS beamforming solutions with closed-form updates per iteration, leading to a highly computationally efficient solution. Simulation results show the efficacy of our proposed algorithms in both performance and computational cost compared to other alternative methods.

Problem

• Minimize transmit power while meeting user QoS targets
• Optimize joint BS and RIS beamforming for multicasting
• Develop fast algorithms with linear computational complexity

Innovation

• Fast alternating multicast beamforming (AMBF) algorithm
• First-order projected subgradient algorithm (PSA)
• Alternating PSA (APSA) for weighted MMF design