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Angular-Domain Massive MIMO Detection: Algorithm, Implementation, and Design Tradeoffs

Mahdavi, Mojtaba (author)
Lund University,Lunds universitet,Institutionen för elektro- och informationsteknik,Institutioner vid LTH,Lunds Tekniska Högskola,Integrerade elektroniksystem,Forskargrupper vid Lunds universitet,Department of Electrical and Information Technology,Departments at LTH,Faculty of Engineering, LTH,Integrated Electronic Systems,Lund University Research Groups
Edfors, Ove (author)
Lund University,Lunds universitet,Institutionen för elektro- och informationsteknik,Institutioner vid LTH,Lunds Tekniska Högskola,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Department of Electrical and Information Technology,Departments at LTH,Faculty of Engineering, LTH,Communications Engineering,Lund University Research Groups
Öwall, Viktor (author)
Lund University,Lunds universitet,Institutionen för elektro- och informationsteknik,Institutioner vid LTH,Lunds Tekniska Högskola,Integrerade elektroniksystem,Forskargrupper vid Lunds universitet,Department of Electrical and Information Technology,Departments at LTH,Faculty of Engineering, LTH,Integrated Electronic Systems,Lund University Research Groups
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Liu, Liang (author)
Lund University,Lunds universitet,Institutionen för elektro- och informationsteknik,Institutioner vid LTH,Lunds Tekniska Högskola,System på chips (master),Utbildningsprogram, LTH,Integrerade elektroniksystem,Forskargrupper vid Lunds universitet,Department of Electrical and Information Technology,Departments at LTH,Faculty of Engineering, LTH,Embedded Electronics Engineering (M.Sc.),Educational programmes, LTH,Faculty of Engineering, LTH,Integrated Electronic Systems,Lund University Research Groups
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 (creator_code:org_t)
2020
2020
English 14 s.
In: IEEE Transactions on Circuits and Systems I: Regular Papers. - 1558-0806. ; 67:6, s. 1948-1961
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • In massive multiple-input multiple-output (MIMO) systems, the large size of channel state information (CSI) matrix significantly increases the computational complexity of uplink detection and size of required memory to store the channel data. To address these challenges, we propose to perform detection in the angular domain, where the channel information can be presented in a more condensed way. The underlying idea is to exploit the sparsity of massive MIMO channel in the angular domain to reduce the size of CSI matrix by selecting dominant beams. Then, an angular-domain linear detector followed by a non-linear post-processing scheme is proposed to perform detection using the reduced-size CSI. Evaluated using measured massive MIMO channels, our method results in 35%-73% reduction in complexity and required memory compared to traditional detectors while it achieves better performance. Moreover, this paper provides a framework, which trades between performance, complexity, and size of required memory. As a proof of concept, we implement the angular-domain detector in a 28 nm FD-SOI CMOS for a massive MIMO with 128 antennas communicating with up to 16 users. Synthesis result shows that our design attains a throughput of 2240 Mbps with an area of 829 k gates.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Keyword

Massive MIMO Detection
5G New Radio
Angular-domain Processing
CMOS Technology
Channel Sparsity
VLSI Implementation
Digital Baseband Processing

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Mahdavi, Mojtaba
Edfors, Ove
Öwall, Viktor
Liu, Liang
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ENGINEERING AND TECHNOLOGY
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