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Abstract
Massive MIMO is a promising technique to meet the exponential growth of global mobile data traffic demand. However, contrary to the current systems, energy consumption of next generation networks is required to be load adaptive as the network load varies significantly throughout the day. In this paper, we propose a load adaptive massive MIMO system that varies the number of antennas following the daily load profile (DLP) in order to maximize the downlink energy efficiency (EE). A multi-cell system is considered where each base station (BS) is equipped with a large number of antennas to serve many single antenna users. In order to incorporate DLP, each BS is modeled as an M/G/m/m state dependent queue under the assumption that the network is dimensioned to serve a maximum number of users at the peak load. For a given number of users in a cell, the optimum number of active antennas maximizing EE is derived. The EE maximization problem is formulated in a game theoretic framework where the number of antennas to be used by a BS is determined through best response iteration. This load adaptive system achieves overall 19% higher EE compared to a baseline system where the BSs always run with the fixed number of antennas that is most energy efficient at peak load and that can be switched-off when there is no traffic.
Original language | English |
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Title of host publication | 2015 IEEE Globecom Workshops, GC Wkshps 2015 - Proceedings |
Publisher | IEEE |
Number of pages | 6 |
ISBN (Print) | 978-1-4673-9526-7 |
DOIs | |
Publication status | Published - 18 Feb 2016 |
MoE publication type | A4 Conference publication |
Event | IEEE Globecom Workshops - San Diego, United States Duration: 6 Dec 2015 → 10 Dec 2015 |
Workshop
Workshop | IEEE Globecom Workshops |
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Abbreviated title | GC Wkshps |
Country/Territory | United States |
City | San Diego |
Period | 06/12/2015 → 10/12/2015 |
Keywords
- Energy efficiency
- M/G/m/m Queue
- Massive MIMO
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Dive into the research topics of 'Energy-efficient load-adaptive massive MIMO'. Together they form a unique fingerprint.Projects
- 1 Finished
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Fundamentals of Ultra Dense 5G Networks with Application to Machine Type Communication
Jäntti, R. (Principal investigator), Duan, R. (Project Member), Beyene, Y. (Project Member) & Hossain, M. M. (Project Member)
01/02/2015 → 31/12/2017
Project: Academy of Finland: Other research funding