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ZipTx: Harnessing Partial Packets in 802.11 Networks
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International Conference on Mobile Computing and Networking archive
Proceedings of the 14th ACM international conference on Mobile computing and networking table of contents
San Francisco, California, USA
SESSION: Cross-layer protocols table of contents
Pages 351-362  
Year of Publication: 2008
ISBN:978-1-60558-096-8
Authors
Kate Ching-Ju Lin  National Taiwan University, Taipei, Taiwan Roc
Nate Kushman  Massachusetts Institute of Technology, Cambridge, MA, USA
Dina Katabi  Massachusetts Institute of Technology, Cambridge, MA, USA
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Current wireless protocols retransmit any packet that fails the checksum test, even when most of the bits are correctly received. Prior work has recognized this inefficiency, however the proposed solutions (e.g., PPR, HARQ and SOFT) require changes to the hardware and physical layer, and hence are not usable in today's WLANs and mesh networks. They are further tested in channels with fixed modulation and coding, whereas production 802.11 networks adapt their modulation and codes to maximize their ability to correct erroneous bits.

This paper makes two key contributions: 1) it introduces ZipTx, a software-only solution that harvests the gains from using correct bits in corrupted packets using existing hardware, and 2) it characterizes the true gains of partially correct packets for the entire range of operation of 802.11 networks, and in the presence of adaptive modulation and error correcting codes. We implement ZipTx as a driver extension and evaluate our implementation in both outdoor and indoor environments, showing that ZipTx significantly improves the throughput.


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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Collaborative Colleagues:
Kate Ching-Ju Lin: colleagues
Nate Kushman: colleagues
Dina Katabi: colleagues