Two-dimensional reduction of beam training overhead in crowded 802.11ad based networks

Sihua Shao, Hanbin Zhang, Dimitrios Koutsonikolas, Abdallah Khreishah

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

3 Scopus citations

Abstract

The millimeter-wave (mm-Wave) or 60 GHz technology emerges as an attractive candidate for indoor wireless access in the 5G architecture. Different from 2.4/5 GHz, high signal attenuation requires mm-Wave antenna utilizing directional transmission to enhance beamforming gain. Consequently, time-consuming beamforming training process between mm-Wave nodes significantly increases communication overhead, especially when the environment is crowded since the nodes perform training process in a contention and backoff manner. In this paper, we propose a novel group beam training scheme that enables simultaneous beam training of all the user devices attempting to associate with the access point. Leveraging the angle-of-arrival sparsity in mm-Wave communications, compressed sensing is adopted to further reduce the beam training overhead. To verify the feasibility of group training and the necessity of compressed sensing under certain conditions, we analyze the signal-to-noise ratio measured on a 60 GHz software defined radio testbed in three typical indoor environments: i) corridor; ii) conference room; and iii) laboratory. Extensive simulations are also performed to evaluate the recovery performance of compressed sensing in mm-Wave WLANs for different sampling capabilities. Simulation results show that compressed sensing reduces the cost of sector sweep by 50%.

Original languageEnglish (US)
Title of host publicationINFOCOM 2018 - IEEE Conference on Computer Communications Workshops
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages680-685
Number of pages6
ISBN (Electronic)9781538659793
DOIs
StatePublished - Jul 6 2018
Event2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018 - Honolulu, United States
Duration: Apr 15 2018Apr 19 2018

Publication series

NameINFOCOM 2018 - IEEE Conference on Computer Communications Workshops

Other

Other2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018
CountryUnited States
CityHonolulu
Period4/15/184/19/18

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

Keywords

  • 60 GHz
  • beamforming
  • compressed sensing
  • group training
  • mm-Wave

Fingerprint Dive into the research topics of 'Two-dimensional reduction of beam training overhead in crowded 802.11ad based networks'. Together they form a unique fingerprint.

Cite this