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Fully Decentralized Massive MIMO Detection Based on Recursive Methods

Sánchez, Jesús Rodríguez (author)
Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
Rusek, Fredrik (author)
Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
Sarajlić, Muris (author)
Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
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Edfors, Ove (author)
Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups
Liu, Liang (author)
Lund University,Lunds universitet,Integrerade elektroniksystem,Forskargrupper vid Lunds universitet,Integrated Electronic Systems,Lund University Research Groups
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 (creator_code:org_t)
2019
2019
English 6 s.
In: Proceedings of the IEEE Workshop on Signal Processing Systems, SiPS 2018. - 9781538663189 ; 2018-October, s. 53-58
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Algorithms for Massive MIMO uplink detection typically rely on a centralized approach, by which baseband data from all antennas modules are routed to a central node in order to be processed. In case of Massive MIMO, where hundreds or thousands of antennas are expected in the base-station, this architecture leads to a bottleneck, with critical limitations in terms of interconnection bandwidth requirements. This paper presents a fully decentralized architecture and algorithms for Massive MIMO uplink based on recursive methods, which do not require a central node for the detection process. Through a recursive approach and very low complexity operations, the proposed algorithms provide a sequence of estimates that converge asymptotically to the zero-forcing solution, without the need of specific hardware for matrix inversion. The proposed solution achieves significantly lower interconnection data-rate than other architectures, enabling future scalability.

Subject headings

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

Keyword

Decentralized
Detection and zero-forcing
Gradient Descent
Massive MIMO
Recursive Least Squares
Stochastic Approximation

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Rusek, Fredrik
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Edfors, Ove
Liu, Liang
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