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Exploring Indoor White Spaces in Metropolises

Published: 21 August 2017 Publication History

Abstract

It is a promising vision to exploit white spaces, that is, vacant VHF and UHF TV channels, to meet the rapidly growing demand for wireless data services in both outdoor and indoor scenarios. While most prior works have focused on outdoor white space, the indoor story is largely open for investigation. Motivated by this observation and discovering that 70% of the spectrum demand comes from indoor environment, we carry out a comprehensive study to explore indoor white spaces. We first conduct a large-scale measurement study and compare outdoor and indoor TV spectrum occupancy at 30+ diverse locations in a typical metropolis—Hong Kong. Our results show that abundant white spaces are available in different areas in Hong Kong, which account for more than 50% and 70% of the entire TV spectrum in outdoor and indoor scenarios, respectively. Although there are substantially more white spaces indoors than outdoors, there have been very few solutions for identifying indoor white space. To fill in this gap, we develop the first data-driven, low-cost indoor white space identification system for White-space Indoor Spectrum EnhanceR (WISER), to allow secondary users to identify white spaces for communication without sensing the spectrum themselves. We design the architecture and algorithms to address the inherent challenges. We build a WISER prototype and carry out real-world experiments to evaluate its performance. Our results show that WISER can identify 30%--40% more indoor white spaces with negligible false alarms, as compared to alternative baseline approaches.

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Published In

cover image ACM Transactions on Intelligent Systems and Technology
ACM Transactions on Intelligent Systems and Technology  Volume 9, Issue 1
Regular Papers and Special Issue: Data-driven Intelligence for Wireless Networking
January 2018
258 pages
ISSN:2157-6904
EISSN:2157-6912
DOI:10.1145/3134224
  • Editor:
  • Yu Zheng
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 21 August 2017
Accepted: 01 March 2017
Revised: 01 February 2017
Received: 01 November 2016
Published in TIST Volume 9, Issue 1

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Author Tags

  1. TV white spaces
  2. clustering algorithms
  3. sensor placement

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  • Research-article
  • Research
  • Refereed

Funding Sources

  • University Grants Committee of the Hong Kong Special Administrative Region, China
  • General Research
  • National Basic Research Program of China

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