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Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
University of Pisa, Italy; University of Paris Saclay, France.
Huawei Technology Co Ltd, France.
2016 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 34, no 4, 832-847 p.Article in journal (Refereed) PublishedText
Abstract [en]

What would a cellular network designed for maximal energy efficiency look like? To answer this fundamental question, tools from stochastic geometry are used in this paper to model future cellular networks and obtain a new lower bound on the average uplink spectral efficiency. This enables us to formulate a tractable uplink energy efficiency (EE) maximization problem and solve it analytically with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor. The closed-form expressions obtained from this general EE maximization framework provide valuable insights on the interplay between the optimization variables, hardware characteristics, and propagation environment. Small cells are proved to give high EE, but the EE improvement saturates quickly with the BS density. Interestingly, the maximal EE is achieved by also equipping the BSs with multiple antennas and operate in a "massive MIMO" fashion, where the array gain from coherent detection mitigates interference and the multiplexing of many users reduces the energy cost per user.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2016. Vol. 34, no 4, 832-847 p.
Keyword [en]
Energy efficiency; massive MIMO; small cells; stochastic geometry
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-130309DOI: 10.1109/JSAC.2016.2544498ISI: 000377928500012OAI: oai:DiVA.org:liu-130309DiVA: diva2:950493
Note

Funding Agencies|ELLIIT; Swedish Foundation for Strategic Research; People Programme (Marie Curie Actions) FP7 [PIEF-GA-2012-330731 Dense4Green]; ERC [305123 MORE]

Available from: 2016-07-31 Created: 2016-07-28 Last updated: 2016-07-31

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Björnson, Emil
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