In this paper we investigate interference cancellation to faster identify tags in RFID networks. We explore how interference cancellation can be applied to ALOHA and tree-based iden- tification schemes, its limitations, the extent of achievable improvements, and the overhead incurred to obtain effective gains. Analytical and simulation results show that for an ALOHA-based scheme interference cancellation allows us to identify nearly 23% of tags without directly interrogating them. This speeds up tag identification (over 20% faster) while producing little overhead. For a tree-based scheme nearly 50% of the tags are identified by exploiting interference cancellation, resulting in an improvement of the identification rate of over 20%. Finally, we propose an enhancement of the tree-based scheme with interference cancellation that achieves a further identification speed up of 50%. Copyright 2011 ACM.
Interference cancellation-based RFID tags identification / Kumar, Raju; Thomas F., La Porta; Maselli, Gaia; Petrioli, Chiara. - (2011), pp. 111-118. (Intervento presentato al convegno 14th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM'11 tenutosi a Miami, FL nel 31 October 2011 through 4 November 2011) [10.1145/2068897.2068919].
Interference cancellation-based RFID tags identification
MASELLI, GAIA;PETRIOLI, Chiara
2011
Abstract
In this paper we investigate interference cancellation to faster identify tags in RFID networks. We explore how interference cancellation can be applied to ALOHA and tree-based iden- tification schemes, its limitations, the extent of achievable improvements, and the overhead incurred to obtain effective gains. Analytical and simulation results show that for an ALOHA-based scheme interference cancellation allows us to identify nearly 23% of tags without directly interrogating them. This speeds up tag identification (over 20% faster) while producing little overhead. For a tree-based scheme nearly 50% of the tags are identified by exploiting interference cancellation, resulting in an improvement of the identification rate of over 20%. Finally, we propose an enhancement of the tree-based scheme with interference cancellation that achieves a further identification speed up of 50%. Copyright 2011 ACM.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
