Decentralized Massive MIMO Processing Exploring Daisy-Chain Architecture and Recursive Algorithms

Research output: Contribution to journalArticle

Abstract

Algorithms for Massive MIMO uplink detection and downlink precoding typically rely on a centralized approach, by which baseband data from all antenna modules are routed to a central node in order to be processed. In the case of Massive MIMO, where hundreds or thousands of antennas are expected in the base-station, said routing becomes a bottleneck since interconnection throughput is limited. This paper presents a fully decentralized architecture and an algorithm for Massive MIMO uplink detection and downlink precoding based on the Coordinate Descent (CD) method, which does not require a central node for these tasks. Through a recursive approach and very low complexity operations, the proposed algorithm provides a good trade-off between performance, interconnection throughput and latency. Further, our proposed solution achieves significantly lower interconnection data-rate than other architectures, enabling future scalability.

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Signal Processing

Keywords

  • coordinate descent, decentralized architecture, detection, inter-connection data-rate, kaczmarz, Massive MIMO, precoding, SINR, zero-forcing
Original languageEnglish
Article number8960442
Pages (from-to)687-700
Number of pages14
JournalIEEE Transactions on Signal Processing
Volume68
Publication statusPublished - 2020
Publication categoryResearch
Peer-reviewedYes