Probabilistic loss differentiation for IEEE 802.11 wireless networks

Song Yilin*, Sun Yi, Li Zhongcheng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We start this paper by answering the questions: What requirements should a good Loss Differentiation Mechanism (LD) for 802.11 networks in IoT meet? Do the existing LDs work well in 802.11 networks when moving towards IoT? Then we present the four properties that a LD used in IoT should own and the two-folded factors that we should consider when designing such a LD. Thereby, a novel LD is proposed utilizing the backoff frozen event to reveal collision probability. Our mechanism works efficiently with standard 802.11; only practical statistics information is needed. In addition, our mechanism can be done solely by the sender without introducing extra signaling overhead. Extensive simulations show that our mechanism can be applicable to different scenarios in 802. 11 WLANs.

Original languageEnglish
Pages (from-to)156-163
Number of pages8
JournalChina Communications
Issue number1
Publication statusPublished - Jan 2011
Externally publishedYes


  • IEEE 802.11 WLANs
  • IoT
  • LD


Dive into the research topics of 'Probabilistic loss differentiation for IEEE 802.11 wireless networks'. Together they form a unique fingerprint.

Cite this