Deep Learning for TDD and FDD Massive MIMO: Mapping Channels in Space and Frequency

Muhammad Alrabeiah, Ahmed Alkhateeb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Can we map the channels at one set of antennas and one frequency band to the channels at another set of antennas-possibly at a different location and a different frequency band If this channel-to-channel mapping is possible, we can expect dramatic gains for massive MIMO systems. For example, in FDD massive MIMO, the uplink channels can be mapped to the downlink channels or the downlink channels at one subset of antennas can be mapped to the downlink channels at all the other antennas. This can significantly reduce (or even eliminate) the downlink training/feedback overhead. In the context of cell-free/distributed massive MIMO systems, this channel mapping can be leveraged to reduce the fronthaul signaling overheadIn this paper, we introduce the new concept of channel mapping in space and frequency, where the channels at one set of antennas and one frequency band are mapped to the channels at another set of antennas and frequency band. First, we prove that this channel-to-channel mapping function exists under certain conditions. Then, we leverage the powerful learning capabilities of deep neural networks to efficiently learn this non-trivial channel mapping function, which is also confirmed by the simulation results.

Original languageEnglish (US)
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1465-1470
Number of pages6
ISBN (Electronic)9781728143002
DOIs
StatePublished - Nov 2019
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: Nov 3 2019Nov 6 2019

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2019-November
ISSN (Print)1058-6393

Conference

Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
Country/TerritoryUnited States
CityPacific Grove
Period11/3/1911/6/19

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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