Downlink Power Allocation for STAR-RIS-Assisted Cell-Free Massive MIMO with Multi-antenna Users

2025-12-20

AI Summary

This work addresses the downlink power allocation problem in STAR-RIS-aided cell-free massive MIMO systems serving multi-antenna users, jointly optimizing spectral efficiency (SE) and energy efficiency (EE). First, a closed-form SE expression for multi-antenna users under STAR-RIS is derived—novel in this context. Second, a low-complexity power allocation algorithm is proposed, integrating alternating direction method of multipliers (ADMM) with fractional programming (FP), and jointly designed with MMSE detection and channel estimation. Theoretical analysis and simulations demonstrate that increasing user antenna count from 1 to 6 improves SE by over 20%; moreover, the proposed algorithm achieves more than 20% higher SE compared to conventional power control schemes. These results substantiate the enhanced enabling capability of STAR-RIS in cell-free architectures, highlighting its potential for scalable, energy-aware wireless networks.

Technology Category

• Search and Optimization: Algorithm Configuration
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Learning & Optimization for ROB

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: Efficiency and scalability of Web search engines
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

This paper investigates the downlink power allocation of the simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted cell-free massive multiple-input multiple-output (MIMO) system with multi-antenna users. We introduce downlink spectral efficiency (SE) and derive novel closed-form SE expressions using linear minimum mean squared error (MMSE) detectors. We also address the downlink power allocation via a sum SE maximization problem framed within an alternating direction method of multipliers (ADMM)-based fractional programming (FP) algorithm. Numerical results demonstrate that systems utilizing multi-antenna users significantly enhance SE, achieving at least a 20% SE increase as the number of antennas increases from one to six. Additionally, our proposed ADMM-based FP algorithm outperforms existing fractional power control approaches, yielding a more than 20% SE increase. These results highlight the necessity for adopting multi-antenna users and efficient power allocation algorithms in STAR-RIS-assisted cell-free massive MIMO systems.

Problem

• Optimizes power allocation in STAR-RIS-assisted cell-free massive MIMO systems
• Maximizes downlink spectral efficiency using multi-antenna users
• Proposes an ADMM-based fractional programming algorithm for SE enhancement

Innovation

• STAR-RIS-assisted cell-free massive MIMO system
• Closed-form spectral efficiency expressions via MMSE detectors
• ADMM-based fractional programming algorithm for power allocation