Randomized multi-channel interrogation algorithm for large-scale RFID systems
Mohsenian-Rad AH, Shah-Mansouri V, Wong VW, Schober R (2009)
Publication Type: Conference contribution
Publication year: 2009
Conference Proceedings Title: GLOBECOM - IEEE Global Telecommunications Conference
Event location: Honolulu, HI
ISBN: 9781424441488
DOI: 10.1109/GLOCOM.2009.5425452
Abstract
A radio frequency identification (RFID) system consists of a set of readers and several objects, equipped with small computer chips, called tags. In a dense RFID system, where several readers are placed together to improve the read rate and correctness, readers and tags can frequently experience packet collision. A common approach to avoid collision is to use a distinct frequency channel for interrogation for each reader. Various multi-channel anti-collision protocols have been proposed for RFID readers. However, due to their heuristic nature, most algorithms may not fully utilize the achievable system performance. In this paper, we develop an optimization-based distributed randomized multi-channel interrogation algorithm, called FDFA, for large-scale RFID systems. For this purpose, we develop elaborate models for reader-to-tag and reader-to-reader collision problems. FDFA algorithm is guaranteed to find a local optimum of a max-min fair resource allocation problem to balance the processing load among readers. Simulation results show that FDFA has a significantly better performance than the existing heuristic algorithms in terms of the number of successful interrogations. It also better utilizes the frequency spectrum.
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APA:
Mohsenian-Rad, A.H., Shah-Mansouri, V., Wong, V.W., & Schober, R. (2009). Randomized multi-channel interrogation algorithm for large-scale RFID systems. In GLOBECOM - IEEE Global Telecommunications Conference. Honolulu, HI, US.
MLA:
Mohsenian-Rad, Amir Hamed, et al. "Randomized multi-channel interrogation algorithm for large-scale RFID systems." Proceedings of the 2009 IEEE Global Telecommunications Conference, GLOBECOM 2009, Honolulu, HI 2009.
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