Toward Optimal RFID Frame Lengths

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In dense radio frequency identification (RFID) systems, reducing reading times is crucial. For tag anti-collision management, most RFID systems rely on Frame Slotted ALOHA (FSA). The most common method used to reduce the reading time for large tag populations is the optimization of the number of slots per frame. Each slot in real RFID systems has a different duration determined by its type (idle, successful, or colliding). Furthermore, by detecting the strongest transponder, colliding slots can be converted into successful slots, a phenomenon known as the capture effect. The strongest tag reply can also be intentionally detected by enhancing the reader’s capabilities with collision recovery. RFID readers may also be capable of identifying slot types using the physical layer and reducing the colliding slot time because in this case, the reader can immediately terminate the connection as there is no reason to reply with an invalid acknowledge and wait for the time-out. This paper presents an exhaustive analysis of the effect of slot type identification and capture probability on the frame length in the presence of different tag cardinality estimation techniques. Additionally, the effect of the new optimized frame length on the total reading time reduction is addressed with different tag encoding schemes. Theoretically, experimental results for FM0 encoding show that our technique achieves a total reading time reduction between 5.5% and 11.3% over methods that do not take into account slot type identification in the frame length optimization. For Miller encoding scheme with M=2,4, and 8 the reading time is decreased by 9%, 6%, and 1% respectively. The maximum reading time reductions are achieved at collision recovery probabilities values of 0.4 for FM0 and Miller with M=2 and 0.45 & 0.6 for M=4, and M=8, respectively. In case the reader does not have any collision recovery capability and the Shoute algorithm is used to estimate the tag cardinality, the maximum reading time reductions dropped to 3.9%, 2.6%, 1.7%, and 1.3% for FM0, Miller encoding scheme with M=2,4, and 8, respectively. However, if a more optimized tag cardinality estimation technique is used such as the Schoute algorithm, the maximum reading time reductions are 7.8%, 4.8%, 3.3%, and 2.4% for FM0, Miller encoding scheme with M=2,4 and 8, respectively.