Measurement-based models of delivery and interference in static wireless networks
By Charles Reis, Ratul Mahajan, Maya Rodrig, David Wetherall, J. Zahorjan. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2006
395 citations recorded by the source corpus.
We present practical models for the physical layer behaviors of packet reception and carrier sense with interference in static wireless networks. These models use measurements of a real network rather than abstract RF propagation models as the basis for accuracy in complex environments. Seeding our models requires N trials in an N node network, in which each sender transmits in turn and receivers measure RSSI values and packet counts, both of which are easily obtainable. The models then predict packet delivery and throughput in the same network for different sets of transmitters with the same node placements. We evaluate our models for the base case of two senders that broadcast packets simultaneously. We find that they are effective at predicting when there will be significant interference effects. Across many predictions, we obtain an RMS error for 802.11a and 802.11b of a half and a third, respectively, of a measurement-based model that ignores interference.
Subfields: Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/81887be9e2a33b163ac3494cf995221f1b80e2a1
How researchers see this paper
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In Computer Networks and Communications
- Dina Katabi
- Sachin Rajsekhar Katti
- Hari Balakrishnan
- Muriel Médard
- David Wetherall
- Wenjun Hu
- Daniel Halperin
- Anand Prabhu Subramanian
Citations in the corpus
- Predictable 802.11 packet delivery from wireless channel measurements (2010, background): “11b [3, 22] found RSSI to be a weak predictor of packet delivery that improved when receivers were calibrated for thermal conditions and manufacturing variability.”
- Minimum Interference Channel Assignment in Multi-Radio Wireless Mesh Networks (2007, methodology): “Section VII) can be computed using methods similar to recent ly reported measurement-based techniques in [21, 22].”
- TRUST: A General Framework for Truthful Double Spectrum Auctions (2009, methodology): “If the condition is modeled by the physical Signal to Interference and Noise Ratio (SINR) [18], TRUST finds multiple sets of buyers who can transmit simultaneously and maintain an adequate received SINR [3].”
- Symbol-level network coding for wireless mesh networks (2008, methodology): “Furthermore, unlike prior proposals [24, 20] that try to predict packet delivery rates using a SINR model, MIXIT’s model predicts symbol delivery likelihoods.”