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Measurement-based models of delivery and interference in static wireless networks
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Source Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications table of contents
Pisa, Italy
SESSION: Wireless table of contents
Pages: 51 - 62  
Year of Publication: 2006
ISBN:1-59593-308-5
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Authors
Charles Reis  University of Washington
Ratul Mahajan  Microsoft Research
Maya Rodrig  University of Washington
David Wetherall  University of Washington
John Zahorjan  University of Washington
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  31

Collaborative Colleagues:
Charles Reis: colleagues
Ratul Mahajan: colleagues
Maya Rodrig: colleagues
David Wetherall: colleagues
John Zahorjan: colleagues