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An Opportunistic Backoff Scheme for Dense IEEE 802.11 WLANs

In English

Författare

Summary, in English

In dense deployments, the performance of IEEE 802.11 Wireless Local Area Networks (WLANs) depends on the development of efficient contention resolution mechanisms since the collision probability can be high even with low number of users with the current 802.11 MAC mechanism. Also, the current 802.11 MAC is not opportunistic in the sense that it does not consider channel quality and traffic load of users, which can greatly degrade the network capacity. In this paper, we propose a new backoff scheme which performs well for dense networks resulting in low collision probability. Also, our backoff scheme opportunistically gives higher priority to users with high traffic load and better channel conditions, and thus reduces unnecessary contention. We analytically show that the performance of our backoff algorithm can be pushed to the maximum throughput in exchange for longer backoff delay, which is compensated with reduced number of collisions. We evaluate our algorithm in OMNeT++, and show that compared to the legacy 802.11 Distributed coordination Function (DCF) the aggregated network throughput can be increased up to 70\% by using our algorithm. Also, compared with legacy DCF, the maximum number of supportable users is much higher and the end-to-end delay performance is better with our backoff scheme for dense scenarios under the same traffic conditions.

Publiceringsår

2016

Språk

Engelska

Publikation/Tidskrift/Serie

Proc. of the IEEE GLOBECOM'15 WS Enabling Technologies in Future Wireless Local Area Network (ETFWLALN)

Dokumenttyp

Konferensbidrag

Ämne

  • Communication Systems
  • Telecommunications

Nyckelord

  • IEEE 802.11
  • dense networks
  • opportunistic 802.11 DCF

Conference name

IEEE Global Communication Conference (GLOBECOM), 2015

Conference date

2015-12-06 - 2015-12-10

Conference place

San Diego, California, United States

Status

Published

Projekt

  • ELLIIT LU P01: WP2 Networking solutions

ISBN/ISSN/Övrigt

  • ISBN: 9781467395267