research-article

Surviving wi-fi interference in low power ZigBee networks

Authors:

Chieh-Jan Mike Liang,

Nissanka Bodhi Priyantha,

Andreas TerzisAuthors Info & Claims

SenSys '10: Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems

Pages 309 - 322

https://doi.org/10.1145/1869983.1870014

Published: 03 November 2010 Publication History

Abstract

Frequency overlap across wireless networks with different radio technologies can cause severe interference and reduce communication reliability. The circumstances are particularly unfavorable for ZigBee networks that share the 2.4 GHz ISM band with WiFi senders capable of 10 to 100 times higher transmission power. Our work first examines the interference patterns between ZigBee and WiFi networks at the bit-level granularity. Under certain conditions, ZigBee activities can trigger a nearby WiFi transmitter to back off, in which case the header is often the only part of the Zig-Bee packet being corrupted. We call this the symmetric interference regions, in comparison to the asymmetric regions where the ZigBee signal is too weak to be detected by WiFi senders, but WiFi activity can uniformly corrupt any bit in a ZigBee packet. With these observations, we design BuzzBuzz to mitigate WiFi interference through header and payload redundancy. Multi-Headers provides header redundancy giving ZigBee nodes multiple opportunities to detect incoming packets. Then, TinyRS, a full-featured Reed Solomon library for resource-constrained devices, helps decoding polluted packet payload. On a medium-sized testbed, BuzzBuzz improves the ZigBee network delivery rate by 70%. Furthermore, BuzzBuzz reduces ZigBee retransmissions by a factor of three, which increases the WiFi throughput by 10%.

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Yao JHuang HSu JXie RZheng XWu K(2024)Enabling Cross-Technology Coexistence for ZigBee Devices Through Payload EncodingIEEE Transactions on Mobile Computing10.1109/TMC.2023.334583023:8(8289-8306)Online publication date: Aug-2024
https://doi.org/10.1109/TMC.2023.3345830
Lin CLi GZhang XGuo L(2024)RF Sensing-enabled Interference Mitigation for Wi-Fi-based IoT Systems: A Deep Learning Approach2024 IEEE Conference on Communications and Network Security (CNS)10.1109/CNS62487.2024.10735625(1-9)Online publication date: 30-Sep-2024
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Index Terms

Surviving wi-fi interference in low power ZigBee networks
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

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Published In

cover image ACM Conferences

SenSys '10: Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems

November 2010

461 pages

ISBN:9781450303446

DOI:10.1145/1869983

General Chair:
Jan Beutel
ETH Zurich, Switzerland
,
Program Chairs:
Deepak Ganesan
University of Massachusetts, Amherst
,
Jack Stankovic
University of Virginia

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 03 November 2010

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Division of Computer and Network Systems

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SenSys10

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SenSys10: The 8th ACM Conference on Embedded Network Sensor Systems

November 3 - 5, 2010

Zürich, Switzerland

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Overall Acceptance Rate 198 of 990 submissions, 20%

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https://doi.org/10.1109/TVT.2024.3467109
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https://doi.org/10.1109/TMC.2023.3345830
Lin CLi GZhang XGuo L(2024)RF Sensing-enabled Interference Mitigation for Wi-Fi-based IoT Systems: A Deep Learning Approach2024 IEEE Conference on Communications and Network Security (CNS)10.1109/CNS62487.2024.10735625(1-9)Online publication date: 30-Sep-2024
https://doi.org/10.1109/CNS62487.2024.10735625
Wang XHuang JShi BOu ZLuo GKong LZhang DXu CCosta XAl Hassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)RF-SIFTER: Sifting Signals at Layer-0.5 to Mitigate Wideband Cross-Technology Interference for IoTProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3592513(1-14)Online publication date: 2-Oct-2023
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Yao JLou WXie RJiao XWu K(2023)Mitigating Cross-Technology Interference Through Fast Signal IdentificationIEEE Transactions on Vehicular Technology10.1109/TVT.2022.321366372:2(2521-2534)Online publication date: Feb-2023
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Iordache VGheorghiu RMinea MBurețea LObreja L(2023)Increasing Data Transmission Reliability using Pseudo-spread-spectrum Short-Range Radio Networks2023 IEEE 29th International Symposium for Design and Technology in Electronic Packaging (SIITME)10.1109/SIITME59799.2023.10430491(96-101)Online publication date: 18-Oct-2023
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