User-Centric Clustering Under Fairness Scheduling in Cell-Free Massive MIMO Article Swipe

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Fabian Göttsch , Noboru Osawa , Yoshiaki Amano , Issei Kanno , Kosuke Yamazaki , Giuseppe Caire · YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2305.08363

We consider fairness scheduling in a user-centric cell-free massive MIMO network, where $L$ remote radio units, each with $M$ antennas, serve $K_{\rm tot} \approx LM$ user equipments (UEs). Recent results show that the maximum network sum throughput is achieved where $K_{\rm act} \approx \frac{LM}{2}$ UEs are simultaneously active in any given time-frequency slots. However, the number of users $K_{\rm tot}$ in the network is usually much larger. This requires that users are scheduled over the time-frequency resource and achieve a certain throughput rate as an average over the slots. We impose throughput fairness among UEs with a scheduling approach aiming to maximize a concave component-wise non-decreasing network utility function of the per-user throughput rates. In cell-free user-centric networks, the pilot and cluster assignment is usually done for a given set of active users. Combined with fairness scheduling, this requires pilot and cluster reassignment at each scheduling slot, involving an enormous overhead of control signaling exchange between network entities. We propose a fixed pilot and cluster assignment scheme (independent of the scheduling decisions), which outperforms the baseline method in terms of UE throughput, while requiring much less control information exchange between network entities.

Type

preprint

Language

en

Landing Page

http://arxiv.org/abs/2305.08363

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https://arxiv.org/pdf/2305.08363

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green

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10

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https://openalex.org/W4376653854

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https://openalex.org/W4376653854

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DOI

https://doi.org/10.48550/arxiv.2305.08363

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Title

User-Centric Clustering Under Fairness Scheduling in Cell-Free Massive MIMO

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Type

preprint

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Language

en

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Publication year

2023

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Publication date

2023-05-15

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Fabian Göttsch, Noboru Osawa, Yoshiaki Amano, Issei Kanno, Kosuke Yamazaki, Giuseppe Caire

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Landing page

https://arxiv.org/abs/2305.08363

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https://arxiv.org/pdf/2305.08363

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Yes

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green

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https://arxiv.org/pdf/2305.08363

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Concepts

Scheduling (production processes), Computer science, Maximum throughput scheduling, Computer network, Throughput, MIMO, Cluster analysis, Proportionally fair, Distributed computing, Round-robin scheduling, Dynamic priority scheduling, Wireless, Mathematical optimization, Telecommunications, Mathematics, Channel (broadcasting), Quality of service, Machine learning

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0

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10

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