The design of an ad-hoc network of readers for a RFID services in large areas may require the deployment of a significant number of interrogating antennas due to the limited range of reader-tag communication. For passive tags, the factors affecting the performance of the whole link depend on many physical and geometrical parameters. The reading region is not only related to the emitted power and to the radiation patterns of reader/tag antennas, but also to the propagation environment. When a number of readers are planned in a network, mutual coverage of read-zones and mutual interference are generally undesired while safety regulation constraints have to be fulfilled in the whole area. This paper introduces simple models of the most relevant electromagnetic aspects involved in the network planning problem and considers an efficient solution based on the Particle Swarm Optimization algorithm. Numerical and experimental results show the effectiveness of the method.
DI GIAMPAOLO, E., Fornì, F., Marrocco, G. (2010). RFID-Network planning by particle swarm optimization. APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL, 25(3), 263-272.
RFID-Network planning by particle swarm optimization
DI GIAMPAOLO, EMIDIO;MARROCCO, GAETANO
2010-03-01
Abstract
The design of an ad-hoc network of readers for a RFID services in large areas may require the deployment of a significant number of interrogating antennas due to the limited range of reader-tag communication. For passive tags, the factors affecting the performance of the whole link depend on many physical and geometrical parameters. The reading region is not only related to the emitted power and to the radiation patterns of reader/tag antennas, but also to the propagation environment. When a number of readers are planned in a network, mutual coverage of read-zones and mutual interference are generally undesired while safety regulation constraints have to be fulfilled in the whole area. This paper introduces simple models of the most relevant electromagnetic aspects involved in the network planning problem and considers an efficient solution based on the Particle Swarm Optimization algorithm. Numerical and experimental results show the effectiveness of the method.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.