Variational Hierarchical Posterior Matching for mmWave Wireless Channels Online Learning

Nabil Akdim, Carles Navarro Manchon, Mustapha Benjillali, Pierre Duhamel

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

4 Citations (Scopus)

Abstract

We propose a beam alignment algorithm that enables initial access establishment between two transceivers equipped with hybrid digital-analog antenna arrays operating in millimeter wave wireless channels. The proposed method builds upon an active channel learning method based on hierarchical posterior matching that was originally proposed for single-sided beam alignment on single path dominant channels. We extend it to the double-sided alignment problem and propose an estimation framework based on variational Bayesian inference that accounts for the uncertainties on the unknown channel complex gain and noise variance. The proposed approach is numerically shown to be resilient to the single path assumption and reaches near optimal beamforming gains with a moderate training overhead, even at low signal-to-noise ratios.
Original languageEnglish
Title of host publication2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Number of pages5
PublisherIEEE
Publication date3 Aug 2020
Article number9154340
ISBN (Print)978-1-7281-5479-4
ISBN (Electronic)978-1-7281-5478-7
DOIs
Publication statusPublished - 3 Aug 2020
Event2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) - Atlanta, United States
Duration: 26 May 202029 May 2020

Conference

Conference2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Country/TerritoryUnited States
CityAtlanta
Period26/05/202029/05/2020
SeriesIEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
ISSN1948-3252

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