Subgroup-Centric Multicast Cell-Free Massive MIMO

IF 6.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Open Journal of the Communications Society Pub Date : 2024-10-29 DOI:10.1109/OJCOMS.2024.3487912
Alejandro De La Fuente;Guillem Femenias;Felip Riera-Palou;Giovanni Interdonato
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Abstract

Cell-free massive multiple-input multiple-output (CF-mMIMO) is an emerging technology for beyond fifth-generation (5G) systems aimed at enhancing the energy and spectral efficiencies of future mobile networks while providing nearly uniform quality of service to all users. Moreover, multicasting has garnered increasing attention in recent years, as physical-layer multicasting proves to be an efficient approach for serving multiple users simultaneously, all with identical service demands while sharing radio resources. A multicast service is typically delivered using either unicast or a single multicast transmission. In contrast, this work introduces a subgroup-centric multicast CF-mMIMO framework that splits the users into several multicast subgroups. The subgroup creation is based on the similarities in the spatial channel characteristics of the multicast users. This framework benefits from efficiently sharing the pilot sequence used for channel estimation and the precoding filters used for data transmission. The proposed framework relies on two scalable precoding strategies, namely, the centralized improved partial MMSE (IP-MMSE) and the distributed conjugate beamforming (CB). Numerical results demonstrate that the centralized IP-MMSE precoding strategy outperforms the CB precoding scheme in terms of sum SE when multicast users are uniformly distributed across the service area. In contrast, in cases where users are spatially clustered, multicast subgrouping significantly enhances the sum spectral efficiency (SE) of the multicast service compared to both unicast and single multicast transmission. Interestingly, in the latter scenario, distributed CB precoding outperforms IP-MMSE, particularly in terms of per-user SE, making it the best solution for delivering multicast content. Heterogeneous scenarios that combine uniform and clustered distributions of users validate multicast subgrouping as the most effective solution for improving both the sum and per-user SE of a multicast CF-mMIMO service.
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以子群为中心的无小区多播大规模多输入多输出(MIMO
无小区大规模多输入多输出(CF-mMIMO)是超越第五代(5G)系统的新兴技术,旨在提高未来移动网络的能效和频谱效率,同时为所有用户提供几乎一致的服务质量。此外,近年来,多播技术日益受到关注,因为物理层多播技术被证明是同时为多个用户提供服务的有效方法,所有用户都有相同的服务需求,同时共享无线电资源。组播服务通常采用单播或单次组播传输方式提供。相比之下,这项工作引入了一种以子组为中心的多播 CF-mMIMO 框架,可将用户分成多个多播子组。子组的创建基于组播用户空间信道特性的相似性。该框架可有效共享用于信道估计的先导序列和用于数据传输的预编码滤波器。所提出的框架依赖于两种可扩展的预编码策略,即集中式改进部分 MMSE(IP-MMSE)和分布式共轭波束成形(CB)。数值结果表明,当组播用户均匀分布在整个服务区域时,集中式 IP-MMSE 预编码策略的 SE 总和优于 CB 预编码方案。相反,在用户空间集群的情况下,与单播和单一组播传输相比,组播分组能显著提高组播服务的总频谱效率(SE)。有趣的是,在后一种情况下,分布式 CB 预编码优于 IP-MMSE,特别是在每用户 SE 方面,使其成为传输组播内容的最佳解决方案。结合用户均匀分布和聚类分布的异构场景验证了多播分组是提高多播 CF-mMIMO 服务总和与单用户 SE 的最有效解决方案。
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来源期刊
CiteScore
13.70
自引率
3.80%
发文量
94
审稿时长
10 weeks
期刊介绍: The IEEE Open Journal of the Communications Society (OJ-COMS) is an open access, all-electronic journal that publishes original high-quality manuscripts on advances in the state of the art of telecommunications systems and networks. The papers in IEEE OJ-COMS are included in Scopus. Submissions reporting new theoretical findings (including novel methods, concepts, and studies) and practical contributions (including experiments and development of prototypes) are welcome. Additionally, survey and tutorial articles are considered. The IEEE OJCOMS received its debut impact factor of 7.9 according to the Journal Citation Reports (JCR) 2023. The IEEE Open Journal of the Communications Society covers science, technology, applications and standards for information organization, collection and transfer using electronic, optical and wireless channels and networks. Some specific areas covered include: Systems and network architecture, control and management Protocols, software, and middleware Quality of service, reliability, and security Modulation, detection, coding, and signaling Switching and routing Mobile and portable communications Terminals and other end-user devices Networks for content distribution and distributed computing Communications-based distributed resources control.
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