1. Multi-User collaborative scheduling in 5G massive MIMO heterogeneous networks
- Author
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Masson, Marie, Altman, Zwi, Altman, Eitan, Altman, Eitan, Orange Labs [Chatillon], Orange Labs, Network Engineering and Operations (NEO ), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Laboratory of Information, Network and Communication Sciences (LINCS), and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU) more...
- Subjects
[SPI]Engineering Sciences [physics] ,[SPI.ELEC]Engineering Sciences [physics]/Electromagnetism ,densifica- tion ,[SPI] Engineering Sciences [physics] ,Index Terms-Collaborative scheduling ,Small Cells ,[SPI.ELEC] Engineering Sciences [physics]/Electromagnetism ,Multi-User MIMO ,Massive MIMO ,5G - Abstract
International audience; Macro cell densification with Small Cells (SCs) is an effective solution to cope with traffic increase. To fully benefit from the additional SCs capacity, interference mitigation techniques are needed. Densification in 5G networks with Massive Multiple Input Multiple Output (M-MIMO) deployment needs to rethink interference mitigation to account for highly focused beams and MultiUser (MU) scheduling. This paper presents a low complexity collaborative Proportional Fair (PF) based scheduling that maximizes the throughput and improves fairness of the heterogeneous network. The solution is based on the calculation of a loss factor indicator that each SC provides to the macro cell at each scheduling period. These indicators allow the macro cell MU scheduler to efficiently select the set of users for scheduling, leading to a significant improvement in performance. Numerical results illustrate the interest of the collaborative solution. more...
- Published
- 2020