Tag anti-collision algorithms for active and passive RFID networks with foresight
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In the world where initiatives to automate jobs are becoming a norm, it is no surprise that the interest in radio frequency identification (RFID) networks has grown exponentially. With RFID technology, organizations around the world can reduce their workforce and grow their businesses. However, this technology is not yet at a maturity point. For example, in order for a cart full of groceries to go through an unmanned checkout lane, it is crucial that all of the tagged items are read and processed with 100% reliability. Also, the time to process items needs to be fast enough so that customers can pay and be on their way as quickly as possible. In order to achieve speed and reliability, many transmission control protocols have been devised. The most popular protocol with passive RFID equipment manufacturers is Electronic Product Code global (EPCglobal(R)) Class 1 Generation 2, or simply EPC C1G2. Transmission control in the EPC C1G2 protocol is achieved with framed slotted ALOHA (FSA), where tags pick a random slot from choices given by the reader, and when their turn comes, they backscatter their information to the reader. FSA produces three kinds of slots: empty, collided, and successful. Empty and collided slots are categorized under unsuccessful slots, and the time spent on these is considered as wasted time. Several research studies in the past have focused on reducing the occurrence of unsuccessful slots by using new and innovative methods and increasing RFID network throughput. The motivation of this research, however, is to reduce the overall time of reading tags in a passive and active RFID network by minimizing the time spent on unsuccessful slots. This research builds upon methods used in previous research, and proposes three new methods for passive RFID systems and one new method for active RFID systems in order to diminish wasted time on unsuccessful slots.
Thesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science