Regret-minimizing exploration in hetnets with mmWave

Michael Wang, Aveek Dutta, Swapna Buccapatnam, Mung Chiang

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

2 Scopus citations

Abstract

We model and analyze a User-Equipment (UE) based wireless network selection method where individuals act on their stochastic knowledge of the expected behavior off their available networks. In particular, we focus on networks with millimeter-wave (mmWave) radio. Modeling mmWave radio access technologies (RATs) as a stochastic 3-state process based on their physical layer characteristics in Line-of-Sight (LOS), Non-Line-of-Sight (NLOS), and Outage states, we make the realistic assumption that users have no knowledge of the statistics of the RATs and must learn these while maximizing the throughput obtained. We develop an online learning-based approach to access network selection: a user-centric Multi-Armed Bandit Problem that incorporates the cost of switching access networks. We develop an online learning policy that groups network access to minimize costs for RAT selection, analyze the regret (loss due to uncertainty) of our algorithm. We also show that our algorithm obtains optimal regret and in numerical examples achieves 24% increase in total throughput compared to existing techniques for high throughput mmWave RATs that vary over a fast timescale.

Original languageEnglish (US)
Title of host publication2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509017324
DOIs
StatePublished - Nov 2 2016
Event13th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2016 - London, United Kingdom
Duration: Jun 27 2016Jun 30 2016

Publication series

Name2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2016

Other

Other13th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2016
CountryUnited Kingdom
CityLondon
Period6/27/166/30/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Instrumentation

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    Wang, M., Dutta, A., Buccapatnam, S., & Chiang, M. (2016). Regret-minimizing exploration in hetnets with mmWave. In 2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2016 [7733013] (2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SAHCN.2016.7733013