The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Predictable 802.11 packet delivery from wireless channel measurements
Open accessAbstract
RSSI is known to be a fickle indicator of whether a wireless link will work, for many reasons. This greatly complicates operation because it requires testing and adaptation to find the best rate, transmit power or other parameter that is tuned to boost performance. We show that, for the first time, wireless packet delivery can be accurately predicted for commodity 802.11 NICs from only the channel measurements that they provide. Our model uses 802.11n Channel State Information measurements as input to an OFDM receiver model we develop by using the concept of effective SNR. It is simple, easy to deploy, broadly useful, and accurate. It makes packet delivery predictions for 802.11a/g SISO rates and 802.11n MIMO rates, plus choices of transmit power and antennas. We report testbed experiments that show narrow transition regions (<2 dB for most links) similar to the near-ideal case of narrowband, frequency-flat channels. Unlike RSSI, this lets us predict the highest rate that will work for a link, trim transmit power, and more. We use trace-driven simulation to show that our rate prediction is as good as the best rate adaptation algorithms for 802.11a/g, even over dynamic channels, and extends this good performance to 802.11n.
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Cites
Fundamentals of Wireless Communication
Tse, D., & Viswanath, P. (2005) · doi:10.1017/cbo9780511807213 · Cited by 13,162
Cited by
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Widar: Decimeter-Level Passive Tracking via Velocity Monitoring with Commodity Wi-Fi
Qian, K., Wu, C., Yang, Z., Liu, Y., & Jamieson, K. (2017) · Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing · doi:10.1145/3084041.3084067 · Cited by 328
A Survey on Human Behavior Recognition Using Channel State Information
Wang, Z., Jiang, K., Hou, Y., Dou, W., Zhang, C., Huang, Z., & Guo, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2949123 · Cited by 149
Wi-Access: Second Factor User Authentication leveraging WiFi Signals
Shah, S. W., & Kanhere, S. S. (2018) · 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2018.8480152 · Cited by 14
“We used another HP 6930P laptop equipped with Intel 5300 NIC as the AP, as the CSI tool works reliably if both transmitter and receiver are equipped with the Intel 5300 NIC [11].”
MethodInfluentialWi-Sign: Device-free Second Factor User Authentication
Shah, S. W., & Kanhere, S. S. (2018) · Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services · doi:10.1145/3286978.3286994 · Cited by 9
Metadata
- Authors
- Halperin, D., Hu, W., Sheth, A., & Wetherall, D.
- Venue
- Proceedings of the ACM SIGCOMM 2010 conference
- Publisher
- ACM
- Published
- 2010-08-30
- Pages
- 159-170
- OpenAlex
- W2168821867
- Cited by
- 595
- References
- 1
- FWCI
- 31.80
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Halperin, D., Hu, W., Sheth, A., & Wetherall, D. (2010). Predictable 802.11 packet delivery from wireless channel measurements. Proceedings of the ACM SIGCOMM 2010 conference. https://doi.org/10.1145/1851182.1851203
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