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Per-antenna hardware optimization and mixed resolution ADCs in uplink massive MIMO
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-2425-952X
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5954-434X
Institute of Electronics, Communications and Information Technology (ECIT), Queen’s University Belfast, .ORCID iD: 0000-0001-9235-7741
2017 (English)In: Conference Record of The Fifty-FirstAsilomar Conference on Signals, Systems & Computers / [ed] Michael B. Matthews, IEEE conference proceedings, 2017, p. 27-31Conference paper, Published paper (Refereed)
Abstract [en]

Massive multiple-input multiple-output (MIMO) is a key technology for next generation wireless networks that deploys many antennas at the base stations (BSs). This requires low-complexity hardware at each antenna branch that, in turn, increases distortions. This work studies the selection of per-antenna hardware quality in terms of analog-to-digital converters (ADCs) resolution. A new achievable spectral efficiency (SE) expression is derived and majorization theory is used to analyze the order preserving properties of the SE and the power consumption with respect to the per-antenna ADC resolutions. That is, given a fixed sum of ADC resolutions across the antenna array, is it preferable to use an equal-ADC over a mixed-ADC approach? The results show that having equal-resolution ADCs across the antenna array maximizes the SE and minimizes the power consumption.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2017. p. 27-31
Series
Signals, Systems & Computers, E-ISSN 2576-2303 ; 2017
Keywords [en]
Distortion, Hardware, MIMO communication, Power demand, Antenna arrays, Complexity theory
National Category
Telecommunications Signal Processing Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-148777DOI: 10.1109/ACSSC.2017.8335129ISI: 000442659900005ISBN: 9781538618233 (electronic)ISBN: 9781538606667 (electronic)ISBN: 9781538618240 (print)OAI: oai:DiVA.org:liu-148777DiVA, id: diva2:1220833
Conference
2017 51st Asilomar Conference on Signals, Systems, and Computers. Pacific Grove, CA, USA. 29 Oct.-1 Nov. 2017
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Foundation for Strategic Research
Note

Funding agencies: EPSRC [EP/P000673/1]

Available from: 2018-06-19 Created: 2018-06-19 Last updated: 2019-06-25Bibliographically approved

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