Joint AP Selection and Power Allocation for Unicast–Multicast Cell-Free Massive MIMO

Joint unicast and multicast transmissions are becoming increasingly important in practical wireless systems, such as Internet of Things networks. This paper investigates a cell-free massive multiple-input multiple-output system that simultaneously supports both transmission types, with multicast serving multiple groups. Exact closed-form expressions for the achievable downlink spectral efficiency (SE) of both unicast and multicast users are derived for zero-forcing and maximum ratio precoding designs. Accordingly, a weighted sum SE (SSE) maximization problem is formulated to jointly optimize the access point (AP) selection and power allocation. The optimization framework accounts for practical constraints, including the maximum transmit power per AP, fronthaul capacity limitations between APs and the central processing unit, and quality-of-service requirements for all users. The resulting non-convex optimization problem is reformulated into a tractable structure, and an accelerated projected gradient (APG)-based algorithm is developed to efficiently obtain near-optimal solutions. As a performance benchmark, a successive convex approximation (SCA)-based algorithm is also implemented. Simulation results demonstrate that the proposed joint optimization approach significantly enhances the SSE across various system setups and precoding strategies. In particular, the APG-based algorithm achieves substantial complexity reduction while maintaining competitive performance, making it well-suited for large-scale practical deployments.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-08-20
DOI
https://doi.org/10.1109/jiot.2025.3600809
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Joint AP Selection and Power Allocation for Unicast–Multicast Cell-Free Massive MIMO

Hyundong Shin, Michail Matthaiou, Hien Quoc Ngo, Mustafa S. Abbas et al.
IEEE Internet of Things Journal
Advanced MIMO Systems Optimization
article

Joint AP Selection and Power Allocation for Unicast–Multicast Cell-Free Massive MIMO

Hyundong Shin, Michail Matthaiou, Hien Quoc Ngo, Mustafa S. Abbas, Zahra Mobini
article en

Abstract

Joint unicast and multicast transmissions are becoming increasingly important in practical wireless systems, such as Internet of Things networks. This paper investigates a cell-free massive multiple-input multiple-output system that simultaneously supports both transmission types, with multicast serving multiple groups. Exact closed-form expressions for the achievable downlink spectral efficiency (SE) of both unicast and multicast users are derived for zero-forcing and maximum ratio precoding designs. Accordingly, a weighted sum SE (SSE) maximization problem is formulated to jointly optimize the access point (AP) selection and power allocation. The optimization framework accounts for practical constraints, including the maximum transmit power per AP, fronthaul capacity limitations between APs and the central processing unit, and quality-of-service requirements for all users. The resulting non-convex optimization problem is reformulated into a tractable structure, and an accelerated projected gradient (APG)-based algorithm is developed to efficiently obtain near-optimal solutions. As a performance benchmark, a successive convex approximation (SCA)-based algorithm is also implemented. Simulation results demonstrate that the proposed joint optimization approach significantly enhances the SSE across various system setups and precoding strategies. In particular, the APG-based algorithm achieves substantial complexity reduction while maintaining competitive performance, making it well-suited for large-scale practical deployments.

IEEE Internet of Things JournalVol. 12(22)
Queen's University Belfast (GB), Kyung Hee University (KR)
UK Research and Innovation, Department for the Economy, European Commission, Queen's University Belfast, National Research Foundation, Queen's University, National Research Foundation of Korea, Iran Telecommunication Research Center, Ministry of Science and ICT, South Korea, Engineering and Physical Sciences Research Council, European Research Council, Institute for Information and Communications Technology Promotion
Openalex Percentile: Top 80%
Advanced MIMO Systems Optimization
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