Conjugate Beamforming Variants for Multicasting in Cell-Free Massive MIMO Systems
Alejandro de la Fuente, Adri\'an Espinosa, Jan Garc\'ia-Morales, Guillem Femenias, Felip Riera-Palou

TL;DR
This paper evaluates various conjugate beamforming variants for multicasting in cell-free massive MIMO systems, highlighting their performance in different user deployment scenarios and providing practical design insights.
Contribution
It introduces and analyzes distributed conjugate beamforming variants, including normalized and enhanced CB, for scalable multicasting in CF-mMIMO systems with subgroup-based user partitioning.
Findings
NCB offers a good performance-complexity balance in most scenarios.
ECB provides extra gains when channel hardening is sufficient.
Subgroup-based multicasting is crucial in clustered and heterogeneous deployments.
Abstract
This paper studies scalable conjugate beamforming (CB) variants for physical-layer multicasting in cell-free massive multiple-input multiple-output (CF-mMIMO) systems. Focusing on fully distributed precoding, we analyze classical CB, normalized CB (NCB), and enhanced CB (ECB) within a subgroup-centric multicast framework. Multicast users are partitioned into subgroups based on large-scale fading similarity, which enables composite channel estimation, pilot reuse, and distributed precoding with low complexity. The performance of the different CB variants is evaluated in terms of aggregated spectral efficiency (ASE) under representative user geometries, including uniformly distributed users, spatially clustered deployments, and heterogeneous scenarios combining hotspots with more dispersed users. Monte Carlo simulations reveal a strong spatial geometry-dependent behavior: unicast…
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