Cell-free Massive MIMO with Sequential Fronthaul Architecture and Limited Memory Access Points

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Main Authors: Ranjbar, Vida, Beerten, Robbert, Moonen, Marc, Pollin, Sofie
Format: Preprint
Published: 2024
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author Ranjbar, Vida
Beerten, Robbert
Moonen, Marc
Pollin, Sofie
author_facet Ranjbar, Vida
Beerten, Robbert
Moonen, Marc
Pollin, Sofie
contents Cell-free massive multiple-input multiple-output (CFmMIMO) is a paradigm that can improve users' spectral efficiency (SE) far beyond traditional cellular networks. Increased spatial diversity in CFmMIMO is achieved by spreading the antennas into small access points (APs), which cooperate to serve the users. Sequential fronthaul topologies in CFmMIMO, such as the daisy chain and multi-branch tree topology, have gained considerable attention recently. In such a processing architecture, each AP must store its received signal vector in the memory until it receives the relevant information from the previous AP in the sequence to refine the estimate of the users' signal vector in the uplink. In this paper, we adopt vector-wise and element-wise compression on the raw or pre-processed received signal vectors to store them in the memory. We investigate the impact of the limited memory capacity in the APs on the optimal number of APs. We show that with no memory constraint, having single-antenna APs is optimal, especially as the number of users grows. However, a limited memory at the APs restricts the depth of the sequential processing pipeline. Furthermore, we investigate the relation between the memory capacity at the APs and the rate of the fronthaul link.
format Preprint
id arxiv_https___arxiv_org_abs_2407_21754
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Cell-free Massive MIMO with Sequential Fronthaul Architecture and Limited Memory Access Points
Ranjbar, Vida
Beerten, Robbert
Moonen, Marc
Pollin, Sofie
Signal Processing
Cell-free massive multiple-input multiple-output (CFmMIMO) is a paradigm that can improve users' spectral efficiency (SE) far beyond traditional cellular networks. Increased spatial diversity in CFmMIMO is achieved by spreading the antennas into small access points (APs), which cooperate to serve the users. Sequential fronthaul topologies in CFmMIMO, such as the daisy chain and multi-branch tree topology, have gained considerable attention recently. In such a processing architecture, each AP must store its received signal vector in the memory until it receives the relevant information from the previous AP in the sequence to refine the estimate of the users' signal vector in the uplink. In this paper, we adopt vector-wise and element-wise compression on the raw or pre-processed received signal vectors to store them in the memory. We investigate the impact of the limited memory capacity in the APs on the optimal number of APs. We show that with no memory constraint, having single-antenna APs is optimal, especially as the number of users grows. However, a limited memory at the APs restricts the depth of the sequential processing pipeline. Furthermore, we investigate the relation between the memory capacity at the APs and the rate of the fronthaul link.
title Cell-free Massive MIMO with Sequential Fronthaul Architecture and Limited Memory Access Points
topic Signal Processing
url https://arxiv.org/abs/2407.21754