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| Main Authors: | , |
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| Format: | Preprint |
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2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.07310 |
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| _version_ | 1866909896618803200 |
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| author | Zaher, Mahmoud Björnson, Emil |
| author_facet | Zaher, Mahmoud Björnson, Emil |
| contents | The growing demand for efficient delivery of common content to multiple user equipments (UEs) has motivated significant research in physical-layer multicasting. By exploiting the beamforming capabilities of massive MIMO, multicasting provides a spectrum-efficient solution that avoids unnecessary intra-group interference. A key challenge, however, is solving the max-min fair (MMF) and quality-of-service (QoS) multicast beamforming optimization problems, which are NP-hard due to the non-convex structure and the requirement for rank-1 solutions. Traditional approaches based on semidefinite relaxation (SDR) followed by randomization exhibit poor scalability with system size, while state-of-the-art successive convex approximation (SCA) methods only guarantee convergence to stationary points. In this paper, we propose an alternating direction method of multipliers (ADMM)-based framework for MMF and QoS multicast beamforming in cell-free massive MIMO networks. The algorithm leverages SDR but incorporates a novel iterative elimination strategy within the ADMM updates to efficiently obtain near-global optimal rank-1 beamforming solutions with reduced computational complexity compared to standard SDP solvers and randomization methods. Numerical evaluations demonstrate that the proposed ADMM-based procedure not only achieves superior spectral efficiency but also scales favorably with the number of antennas and UEs compared to state-of-the-art SCA-based algorithms, making it a practical tool for next-generation multicast systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_07310 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Low-Complexity ADMM-Based Multicast Beamforming in Cell-Free Massive MIMO Systems Zaher, Mahmoud Björnson, Emil Signal Processing The growing demand for efficient delivery of common content to multiple user equipments (UEs) has motivated significant research in physical-layer multicasting. By exploiting the beamforming capabilities of massive MIMO, multicasting provides a spectrum-efficient solution that avoids unnecessary intra-group interference. A key challenge, however, is solving the max-min fair (MMF) and quality-of-service (QoS) multicast beamforming optimization problems, which are NP-hard due to the non-convex structure and the requirement for rank-1 solutions. Traditional approaches based on semidefinite relaxation (SDR) followed by randomization exhibit poor scalability with system size, while state-of-the-art successive convex approximation (SCA) methods only guarantee convergence to stationary points. In this paper, we propose an alternating direction method of multipliers (ADMM)-based framework for MMF and QoS multicast beamforming in cell-free massive MIMO networks. The algorithm leverages SDR but incorporates a novel iterative elimination strategy within the ADMM updates to efficiently obtain near-global optimal rank-1 beamforming solutions with reduced computational complexity compared to standard SDP solvers and randomization methods. Numerical evaluations demonstrate that the proposed ADMM-based procedure not only achieves superior spectral efficiency but also scales favorably with the number of antennas and UEs compared to state-of-the-art SCA-based algorithms, making it a practical tool for next-generation multicast systems. |
| title | Low-Complexity ADMM-Based Multicast Beamforming in Cell-Free Massive MIMO Systems |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2511.07310 |