Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/10998
Title: Energy-Efficient Cell-Free Massive MIMO Through Sparse Large-Scale Fading Processing
Authors: Chen, S.
Zhang, J.
Bjornson, E.
Demir, O.T.
Ai, B.
Keywords: Cell-free massive MIMO; distributed processing; energy efficiency; large-scale fading; sparse optimization
Electric power utilization; Energy efficiency; Mean square error; Optimization; Signal processing; Spectrum efficiency; Cell-free; Cell-free massive MIMO; Distributed database; Distributed processing; Downlink; Large-scale fading; Large-scales; Power demands; Signal-processing; Sparse optimizations; Task analysis; Uplink; Wireless communications; MIMO systems
Issue Date: 2023
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Cell-free massive multiple-input multiple-output (CF mMIMO) systems serve the user equipments (UEs) by geographically distributed access points (APs) by means of joint transmission and reception. To limit the power consumption due to fronthaul signaling and processing, each UE should only be served by a subset of the APs, but it is hard to identify that subset. Previous works have tackled this combinatorial problem heuristically. In this paper, we propose a sparse distributed processing design for CF mMIMO, where the AP-UE association and long-Term signal processing coefficients are jointly optimized. We formulate two sparsity-inducing mean-squared error (MSE) minimization problems and solve them by using efficient proximal approaches with block-coordinate descent. For the downlink, more specifically, we develop a virtually optimized large-scale fading precoding (V-LSFP) scheme using uplink-downlink duality. The numerical results show that the proposed sparse processing schemes work well in both uplink and downlink. In particular, they achieve almost the same spectral efficiency as if all APs would serve all UEs, while the energy efficiency is 2-4 times higher thanks to the reduced processing and signaling. © 2002-2012 IEEE.
URI: https://doi.org/10.1109/TWC.2023.3270299
https://hdl.handle.net/20.500.11851/10998
ISSN: 1536-1276
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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