Cell-Free Beamforming Design for Physical Layer Multigroup Multicasting

In many wireless communication applications, it is desirable to transmit the same data to multiple user equipments (UEs). Physical layer multicasting presents an efficient transmission topology to exploit the beamforming capabilities at the transmitting nodes and broadcast nature of the wireless cha...

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Published in:	IEEE transactions on wireless communications p. 1
Main Authors:	Zaher, Mahmoud, Bjornson, Emil, Petrova, Marina
Format:	Journal Article
Language:	English
Published:	IEEE 2025
Subjects:	Approximation algorithms Array signal processing cell-free massive MIMO convex optimization downlink beamforming Massive MIMO Multicast Multicast algorithms Multicast communication Optimization Quality of service semidefinite relaxation Signal to noise ratio Vectors Wireless communication
ISSN:	1536-1276, 1558-2248, 1558-2248
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Abstract	In many wireless communication applications, it is desirable to transmit the same data to multiple user equipments (UEs). Physical layer multicasting presents an efficient transmission topology to exploit the beamforming capabilities at the transmitting nodes and broadcast nature of the wireless channel to satisfy the demand for the same content from several UEs. An advantage of multicasting is to avoid unnecessary co-channel interference between UEs requesting the same data. The difficulty is to find the suitable beamforming configuration that guarantees an acceptable minimum data rate, among the receiving UE group, to the multicast transmission. This paper addresses the max-min fair multigroup multicast optimization problem and proposes a novel iterative elimination procedure coupled with semidefinite relaxation (SDR) to find the near-optimal rank-1 beamforming vectors in a cell-free massive MIMO (multiple-input multiple-output) network. The proposed optimization procedure significantly improves computational complexity and spectral efficiency compared to common methods that use SDR followed by some randomization procedure and the state-of-the-art difference-of-convex approximation algorithm. The importance of the proposed procedure is that it is applicable to any SDR problem where a low-rank solution is desirable. Further, we propose a low-complexity algorithm that achieves 87% of the optimal rank-1 solution at orders-of-magnitude lower computational time.
AbstractList	In many wireless communication applications, it is desirable to transmit the same data to multiple user equipments (UEs). Physical layer multicasting presents an efficient transmission topology to exploit the beamforming capabilities at the transmitting nodes and broadcast nature of the wireless channel to satisfy the demand for the same content from several UEs. An advantage of multicasting is to avoid unnecessary co-channel interference between UEs requesting the same data. The difficulty is to find the suitable beamforming configuration that guarantees an acceptable minimum data rate, among the receiving UE group, to the multicast transmission. This paper addresses the max-min fair multigroup multicast optimization problem and proposes a novel iterative elimination procedure coupled with semidefinite relaxation (SDR) to find the near-optimal rank-1 beamforming vectors in a cell-free massive MIMO (multiple-input multiple-output) network. The proposed optimization procedure significantly improves computational complexity and spectral efficiency compared to common methods that use SDR followed by some randomization procedure and the state-of-the-art difference-of-convex approximation algorithm. The importance of the proposed procedure is that it is applicable to any SDR problem where a low-rank solution is desirable. Further, we propose a low-complexity algorithm that achieves 87% of the optimal rank-1 solution at orders-of-magnitude lower computational time.
Author	Zaher, Mahmoud Bjornson, Emil Petrova, Marina
Author_xml	– sequence: 1 givenname: Mahmoud orcidid: 0000-0002-6260-7241 surname: Zaher fullname: Zaher, Mahmoud email: mahmoudz@kth.se organization: Division of Communication Systems, KTH Royal Institute of Technology, Stockholm, Sweden – sequence: 2 givenname: Emil orcidid: 0000-0002-5954-434X surname: Bjornson fullname: Bjornson, Emil email: emilbjo@kth.se organization: Division of Communication Systems, KTH Royal Institute of Technology, Stockholm, Sweden – sequence: 3 givenname: Marina orcidid: 0000-0003-3876-2214 surname: Petrova fullname: Petrova, Marina email: petrovam@kth.se organization: Division of Communication Systems, KTH Royal Institute of Technology, Stockholm, Sweden
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Snippet	In many wireless communication applications, it is desirable to transmit the same data to multiple user equipments (UEs). Physical layer multicasting presents...
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SubjectTerms	Approximation algorithms Array signal processing cell-free massive MIMO convex optimization downlink beamforming Massive MIMO Multicast Multicast algorithms Multicast communication Optimization Quality of service semidefinite relaxation Signal to noise ratio Vectors Wireless communication
Title	Cell-Free Beamforming Design for Physical Layer Multigroup Multicasting
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