Collision recovery is considered one of the main potentials for improving bulk reading speed in the UHF radio identification (RFID) system. The collision occurs when two or more tags reply at the same time. State-of-the-art collision recovery algorithms rely on perfect channel state information (CSI), which is unrealistic. Moreover, these algorithms neglect the rate tolerance, that is, the uncertainty in the bit rate of the tag responses. This paper presents a novel algorithm to estimate all tag parameters, such as tag data rate, number of tags per slot, and CSI, using the Matrix Pencil Method (MPM). The proposed system is compatible with the existing EPCglobal Class-1 Gen-2 RFID standard. The accuracy of the proposed algorithm is evaluated with the different encoding schemes of the tag. The estimated parameters are forwarded to MIMO linear receivers to recover the colliding slots to speed up the identification process. The performance of the three linear receivers; Zero Forcing (ZF), Minimum Mean Square Error (MMSE), and Maximum Likelihood (ML) receivers, is evaluated when the CSI is estimated using the proposed algorithm. All receivers perform similarly due to their different sensitivity to the CSI estimation error. The proposed collision recovery system reduces the time for reading a bulk by at least 13% compared to the literature.

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 Schoute 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.

One of the main obstacles for low latency bulk reading in UHF RFID systems is collision occurrence. State-of-the-art high-speed identification methods mostly rely on collision recovery techniques or collision avoidance algorithms. Collision recovery can be done by enhancing the physical layer capabilities to support this feature. Usually, the probability of collision occurrence can be reduced by carefully optimizing the frame length and accurately estimating the number of tags in the interrogation area. In this paper, bulk reading time is reduced by detecting collisions in tag replies. More precisely, the RFID reader identifies slot types using the tag replies spectrum and the deviation in tag data rates which is known as rate tolerance. This novel reader feature distinguishes two types of collided slots; identified collided slots with shorter duration as compared to the non-identified ones. Hence, our technique drastically improves RFID tag reading times. Our experimental results show that the proposed technique can reduce bulk reading times by 10% compared to conventional receivers at SNR greater than 20dB.

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 to reduce the reading time for large tag populations is optimization of the number of slots per frame. The slot duration in real RFID systems is determined by the slot type (idle, successful, or colliding). Furthermore, by detecting the strongest transponder, colliding slots can be transformed to successful slots, a phenomenon known as the capture effect. Additionally, RFID readers might be capable of identifying slot types using the physical layer which reduces the colliding slot time because at this moment the reader can immediately terminate the connection as there is no need to reply with invalid acknowledge and wait for the time-out. In this paper, we provide a novel approach for analytical estimation of the optimal frame length. Our approach yields a novel closed form equation for the frame length that takes into account durations of different slot types, the capture effect, and the probability of slot type identification. 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. However, the reduction in reading time is maximally 9%, 6%, and 1% for Miller encoding scheme with M = 2, 4, and 8, respectively.