FREDI: Robust RSS-based ranging with multipath effect and radio interference

Yu Zhao, Yunhuai Liu, Tingting Yu, Tian He, Chen Qian

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Radio Signal Strength (RSS) based ranging is attractive for mobile device localization due to low cost and easy deployment. In real environments, its accuracy is severely affected by the multipath effect and external radio interference. The well-studied fingerprinting approaches overcome these problems but introduce high overhead in dynamic environments. In this paper, we address these issues using a completely different approach. We propose a new ranging framework called Fredi that exploits the frequency diversity to overcome the multi-path effect solely based on RSS measurements. Specifically, we design a Discrete Fourier Transformation based algorithm and prove that it has the optimal solution under ideal cases. We further make the algorithm be adaptive and robust to address measurement errors and external radio interference, which are inevitable in practice. We implement Fredi on top of the USRP-2 platform and conduct extensive real experiments in three different indoor environments. Experimental results show the superiority performance compared to the traditional methods. The ranging errors are consistently less than 0.5m within 4m distance and 1m within 6m distance in dynamic environments much more accurate than existing solutions using online RSS measures. Other critical factors that influence the accuracy, such as the antenna polarization and Huygens Effect are also discussed and studied.

Original languageEnglish (US)
Pages (from-to)49-63
Number of pages15
JournalComputer Networks
Volume147
DOIs
StatePublished - Dec 24 2018

Bibliographical note

Funding Information:
This work was supported in part by National Science Foundation grants CCF-1652149 , CNS-1701681 , and CNS-1717948 . It was also supported partly by National Natural Science Foundation of China grants 61772026 and 61332018 and National Key R&D Program of China 2018YFB0803400.

Funding Information:
Tian He is currently a full professor in the Department of Computer Science and Engineering at the University of Minnesota-Twin Cities. He received the Ph.D. degree under Professor John A. Stankovic from the University of Virginia, Virginia. Dr. He is the author and co-author of over 280 papers in premier network journals and conferences with over 22,000 citations (H-Index 65). Dr. He is the recipient of the NSF CAREER Award (2009), McKnight Land-Grant Chaired Professorship (2011), George W. Taylor Distinguished Research Award (2015), China NSF Outstanding Overseas Young Researcher I and II (2012 and 2016), and seven best paper awards in international conferences including MobiCom, SenSys, and ICDCS. Dr. He has served a few general/program chair positions in international conferences and on many program committees and also has been an editorial board member for six international journals including ACM Transactions on Sensor Networks, IEEE Transactions on Computers and IEEE/ACM Transactions on Networking. His research includes wireless networks, networked sensing systems, cyber-physical systems, real-time embedded systems and distributed systems, supported by National Science Foundation, IBM, Microsoft and other agencies. He is an IEEE Fellow.

Publisher Copyright:
© 2018 Elsevier B.V.

Keywords

  • DFT
  • Frequency diversity
  • Localization
  • RSS
  • Ranging

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