Energy-efficient load-adaptive massive MIMO

M.M. Hossain, Cicek Cavdar, Emil Björnson, Riku Jäntti

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

8 Citations (Scopus)


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 languageEnglish
Title of host publication2015 IEEE Globecom Workshops, GC Wkshps 2015 - Proceedings
Number of pages6
ISBN (Print)978-1-4673-9526-7
Publication statusPublished - 18 Feb 2016
MoE publication typeA4 Article in a conference publication
EventIEEE Globecom Workshops - San Diego, United States
Duration: 6 Dec 201510 Dec 2015


ConferenceIEEE Globecom Workshops
Abbreviated titleGC Wkshps
CountryUnited States
CitySan Diego


  • Energy efficiency
  • M/G/m/m Queue
  • Massive MIMO

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  • Projects

    Fundamentals of Ultra Dense 5G Networks with Application to Machine Type Communication

    Jäntti, R., Duan, R. & Beyene, Y.


    Project: Academy of Finland: Other research funding

    Cite this

    Hossain, M. M., Cavdar, C., Björnson, E., & Jäntti, R. (2016). Energy-efficient load-adaptive massive MIMO. In 2015 IEEE Globecom Workshops, GC Wkshps 2015 - Proceedings [7414181] IEEE.