Fully Decentralized Massive MIMO Detection Based on Recursive Methods

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding


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.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Signal Processing


  • Decentralized, Detection and zero-forcing, Gradient Descent, Massive MIMO, Recursive Least Squares, Stochastic Approximation
Original languageEnglish
Title of host publicationProceedings of the IEEE Workshop on Signal Processing Systems, SiPS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538663189
Publication statusPublished - 2019 Jan 3
Publication categoryResearch
Event2018 IEEE Workshop on Signal Processing Systems, SiPS 2018 - Cape Town, South Africa
Duration: 2018 Oct 212018 Oct 24


Conference2018 IEEE Workshop on Signal Processing Systems, SiPS 2018
CountrySouth Africa
CityCape Town