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Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO
Linköping Univ, Dept Elect Engn ISY, Linköping, Sweden..ORCID iD: 0000-0002-5954-434x
Univ Pisa, Dipartimento Ingn Informaz, Pisa, Italy.;Univ Paris Saclay, Cent Supelec, Large Syst & Networks Grp LANEAS, F-91192 Gif Sur Yvette, France..ORCID iD: 0000-0002-2577-4091
Huawei Technol Co Ltd, France Res Ctr, Math & Algorithm Sci Lab, Boulogne, France..ORCID iD: 0000-0003-1143-080X
2016 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 34, no 4, p. 832-847Article in journal (Refereed) Published
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, p. 832-847
Keywords [en]
Energy efficiency, massive MIMO, small cells, stochastic geometry
National Category
Signal Processing Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-295932DOI: 10.1109/JSAC.2016.2544498ISI: 000377928500012Scopus ID: 2-s2.0-84969981854OAI: oai:DiVA.org:kth-295932DiVA, id: diva2:1663826
Note

QC 20220620

Available from: 2022-06-02 Created: 2022-06-02 Last updated: 2022-06-25Bibliographically approved

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Björnson, Emil

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