Coded Energy-Efficient Beam-Alignment for Millimeter-Wave Networks

Muddassar Hussain, Nicolo Michelusi

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

2 Scopus citations

Abstract

Millimeter-wave communications rely on narrow-beam transmissions to cope with the strong signal attenuation at these frequencies, thus demanding precise alignment between transmitter and receiver. However, the beam-alignment procedure may entail a huge overhead and its performance may be degraded by detection errors. This paper proposes a coded energy-efficient beam-alignment scheme, robust against detection errors. Specifically, the beam-alignment sequence is designed such that the error-free feedback sequences are generated from a codebook with the desired error correction capabilities. Therefore, in the presence of detection errors, the error-free feedback sequences can be recovered with high probability. The assignment of beams to codewords is designed to optimize energy efficiency, and a water-filling solution is proved. The numerical results with analog beams depict up to 4dB and 8dB gains over exhaustive and uncoded beam-alignment schemes, respectively.

Original languageEnglish (US)
Title of host publication2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages407-412
Number of pages6
ISBN (Electronic)9781538665961
DOIs
StatePublished - Feb 5 2019
Externally publishedYes
Event56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018 - Monticello, United States
Duration: Oct 2 2018Oct 5 2018

Publication series

Name2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018

Conference

Conference56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
Country/TerritoryUnited States
CityMonticello
Period10/2/1810/5/18

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Energy Engineering and Power Technology
  • Control and Optimization

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