User-Heterogeneous Cell-Free Massive MIMO Downlink and Uplink Beamforming via Tensor Decomposition

Autor: Kengo Ando, Hiroki Iimori, Giuseppe Thadeu Freitas de Abreu, Koji Ishibashi
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: IEEE Open Journal of the Communications Society, Vol 3, Pp 740-758 (2022)
Druh dokumentu: article
ISSN: 2644-125X
DOI: 10.1109/OJCOMS.2022.3167101
Popis: We consider a cell-free massive MIMO (CF-mMIMO) system in which multiple access points (APs), connected to a common central processing unit (CPU) through unbounded fronthaul, collaboratively serve multiple users in a heterogeneous scenario in which each user equipment (UE) has a different number of antennas, and therefore is capable of communicating via distinct numbers of digital streams. For such a user-heterogeneous system, new joint transmit (TX)/receive (RX) beamforming (BF) algorithms are then proposed, both for downlink and uplink modes and integrated with two alternative transmit (TX) power and spatial resource allocation strategies, which enable interference-free communications. To that end, a novel tensor decomposition scheme is presented, based on an orthogonality-enforcing modification of the recently-proposed multilinear generalized singular value decomposition (ML-GSVD). Simulation results show both that the new orthogonality-enforcing ML-GSVD (OEML-GSVD) achieves greater accuracy than the previous multilinear generalized singular value decomposition (ML-GSVD) without sacrificing convergence speed, and that the corresponding OEML-GSVD-based proposed beamformers outperform state-of-the-art (SotA) techniques, as well as an equivalent beamformer based on the previous ML-GSVD alternative.
Databáze: Directory of Open Access Journals