Self-learning collision avoidance for wireless networks

Chun Cheng Chen, Eunsoo Seo, Hwangnam Kim, Haiyun Luo

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

21 Citations (Scopus)

Abstract

The limited number of orthogonal channels and the autonomous installations of hotspots and home wireless networks often leave neighboring 802.11 basic service sets (BSS's) operating on the same or overlapping channels, therefore interfering with each other. However, the 802.11 MAC does not work well in resolving inter-BSS interferences due to the well-known hidden/exposed receiver problem, which has been haunting in the research community for more than a decade. In this paper we propose SELECT, an effective and efficient self-learning collision avoidance strategy to address the open hidden/exposed receiver problem in wireless networks. SELECT is based on the observation that carrier sense with received signal strength (RSS) measurements at the sender and the receiver are strongly correlated. A SELECT-enabled sender exploits such correlation using automated on-line learning algorithm, and makes informed judgment of the channel availability at the intended receiver. SELECT achieves collision avoidance at packetlevel time granularity, involves zero communication overhead, requires no hardware support beyond what is available in offthe-shelf 802.11 devices, and easily integrates with the 802.11 DCF. Our evaluation in both analysis and simulations show that SELECT addresses the hidden/exposed receiver problem well. In typical hidden/exposed receiver scenarios SELECT improves the throughput by up to 140% and channel access success ratio by up to 302%, while almost completely eliminating contention-induced data packet drops.

Original languageEnglish
Title of host publicationProceedings - IEEE INFOCOM
DOIs
Publication statusPublished - 2006 Dec 1
Externally publishedYes
EventINFOCOM 2006: 25th IEEE International Conference on Computer Communications - Barcelona, Spain
Duration: 2006 Apr 232006 Apr 29

Other

OtherINFOCOM 2006: 25th IEEE International Conference on Computer Communications
CountrySpain
CityBarcelona
Period06/4/2306/4/29

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture

Cite this

Chen, C. C., Seo, E., Kim, H., & Luo, H. (2006). Self-learning collision avoidance for wireless networks. In Proceedings - IEEE INFOCOM [4146968] https://doi.org/10.1109/INFOCOM.2006.315