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Clustered Cell-Free Networking: A Graph Partitioning Approach

  • Junyuan Wang*
  • , Lin Dai
  • , Lu Yang
  • , Bo Bai
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

73 Downloads (CityUHK Scholars)

Abstract

By moving to millimeter wave (mmWave) frequencies, base stations (BSs) will be densely deployed to provide seamless coverage in sixth generation (6G) mobile communication systems, which, unfortunately, leads to severe cell-edge problem. In addition, with massive multiple-input-multiple-output (MIMO) antenna arrays employed at BSs, the beamspace channel is sparse for each user, and thus there is no need to serve all the users in a cell by all the beams therein jointly. Therefore, it is of paramount importance to develop a flexible clustered cell-free networking scheme that can decompose the whole network into a number of weakly interfered small subnetworks operating independently and in parallel. Given a per-user rate constraint for service quality guarantee, this paper aims to maximize the number of decomposed subnetworks so as to reduce the signaling overhead and system complexity as much as possible. By formulating it as a bipartite graph partitioning problem, a rate-constrained network decomposition (RC-NetDecomp) algorithm is proposed, which can smoothly tune the network structure from the current cellular network with simple beam allocation to a fully cooperative network by increasing the required per-user rate. Simulation results demonstrate that the proposed RC-NetDecomp algorithm outperforms existing baselines in terms of average per-user rate, fairness among users and energy efficiency. © 2023 IEEE.
Original languageEnglish
Pages (from-to)5349-5364
JournalIEEE Transactions on Wireless Communications
Volume22
Issue number8
Online published10 Jan 2023
DOIs
Publication statusPublished - Aug 2023

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 62001330, in part by the Shanghai Sailing Program under Grant 20YF1452600, and in part by the Fundamental Research Funds for the Central Universities. The work of Lin Dai was supported in part by Huawei Technologies Company Ltd., under Grant 9229002; and in part by the City University of Hong Kong Strategic Research Grant under Grant 7005442. An earlier version of this paper was presented in part at the IEEE International Conference on Communications (ICC), Seoul, South Korea, in May 2022 [1] [DOI: 10.1109/ICC45855.2022.9838756].

Research Keywords

  • Antenna arrays
  • Cellular networks
  • Clustered cell-free networking
  • Clustering algorithms
  • Complexity theory
  • graph partitioning
  • Interference cancellation
  • Massive MIMO
  • massive multiple-input-multiple-output (MIMO)
  • Millimeter wave communication
  • network decomposition
  • spectral clustering

Publisher's Copyright Statement

  • COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Wang, J., Dai, L., Yang, L., & Bai, B. (2023). Clustered Cell-Free Networking: A Graph Partitioning Approach. IEEE Transactions on Wireless Communications, 22(8), 5349-5364. https://doi.org/10.1109/TWC.2022.3233444.

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