Radio Frequency Identification (RFID) is one of the key technologies of the Internet of Things. However, during its application, it faces a huge challenge of co-frequency interference cancellation, that is, the tag collision problem. The multi-tag anti-collision problem is modeled as a Blind Source Separation (BSS) problem from the perspective of system communication transmission layer signal processing. In order to reduce the cost of the reader antenna, this paper uses the boundedness of the tag communication signal to propose an underdetermined RFID tag anti-collision method based on Bounded Component Analysis (BCA). This algorithm converts the underdetermined tag into the signal collision model is combined with the BCA mechanism. Verification analysis was conducted using simulation data. The experimental results show that compared with the nonnegative matrix factorization (NMF) algorithm based on minimum correlation and minimum volume constraints, the bounded component analysis method proposed in this article can perform better. Solving the underdetermined collision problem greatly improves the effect of eliminating co-channel interference of tag signals, improves the system bit error rate performance, and reduces the complexity of the underdetermined model system.

Radio Frequency Identification (RFID) is crucial for the Internet of Things, with a key challenge being the efficient prevention of tag collisions for quick identification. This paper presents a novel approach for rapid tag recognition in small to medium-sized warehouses, combining a tag optimization feature set with a tail code recognition mechanism. To minimize the frequency of scanning for duplicate tags and reduce the occurrence of collisions, we construct an optimization feature set based on the reader’s position. This set helps in assessing the likelihood of tag repetition through its linear variation. It also incorporates a tail code mechanism that recognizes only the last 22 digits of the tag’s EPC code, significantly speeding up identification. The tail code length is dynamically adjusted based on the number of tags to maintain uniqueness. Simulation results indicate that our approach significantly reduces the identification of duplicate tags and minimizes the instances of collisions.

Nonnegative Matrix Factorization (NMF) is a promising data-driven matrix decomposition method, and is becoming very active and attractive in machine learning and blind source separation areas. So far NMF algorithm has been widely used in diverse applications, including image processing, anti-collision for Radio Frequency Identification (RFID) systems and audio signal analysis, and so on. However the typical NMF algorithms cannot work well in underdetermined mixture, i.e., the number of observed signals is less than that of source signals. In practical applications, adding suitable constraints fused into NMF algorithm can achieve remarkable decomposition results. As a motivation, this paper proposes to add the minimum volume and minimum correlation constrains (MCV) to the NMF algorithm, which makes the new algorithm named MCV-NMF algorithm suitable for underdetermined scenarios where the source signals satisfy mutual independent assumption. Experimental simulation results validate that the MCV-NMF algorithm has a better performance improvement in solving RFID tag anti-collision problem than that of using the nearest typical NMF method.

In this letter, we consider several optimization problems associated with the configuration of grouping-based framed slotted ALOHA protocols. Closed-form formulas for determining the optimal values of system parameters such as the process termination time and confidence levels for partitioned groups are presented. Further, we address the maximum group size required for meaningful grouping gain and the effectiveness of the grouping technique in light of signaling overhead.

In this paper, we analyze two representative tree-based RFID anti-collision algorithms: the Query Tree protocol and the Binary Search algorithm. Based on the advantages and disadvantages of the two algorithms, we propose and evaluate two optimized anti-collision algorithms: the Optimized Binary Search, which performs better than the Query Tree Protocol with the same tag-side overhead, and the Optimized Binary Search with Multiple Collision Bits Resolution algorithm, which performs the best with an acceptable increase in tag-side processing overhead.

Fast identification is an urgent demand for modern RFID systems. In this paper, we propose a novel algorithm, access probability adjustment based fine-grained Q-algorithm (APAFQ), to enhance the efficiency of RFID identification with low computation overhead. Specifically, instead of estimation accuracy, the target of most proposed anti-collision algorithms, the APAFQ scheme is driven by updating Q value with two different weights, slot by slot. To achieve higher identification efficiency, the reader adopts fine-grained access probability during the identification process. Moreover, based on the responses from tags, APAFQ adjusts the access probability adaptively. Simulations show the superiority of APAFQ over existing Aloha-based algorithms.

Tag collision has a negative impact on the performance of RFID systems. In this letter, we propose an algorithm termed anti-collision protocol based on improved collision detection (ACP-ICD). In this protocol, dual prefixes matching and collision bit detection technique are employed to reduce the number of queries and promptly identify tags. According to the dual prefixes matching method and collision bit detection in the process of collision arbitration, idle slots are eliminated. Moreover, the reader makes full use of collision to improve identification efficiency. Both analytical and simulation results are presented to show that the performance of ACP-ICD outperforms existing anti-collision algorithms.

In many radio frequency identification (RFID) applications, the reader identifies the tags in its scope repeatedly. For these applications, many algorithms, such as an adaptive binary splitting algorithm (ABS), a single resolution blocking ABS (SRB), a pair resolution blocking ABS (PRB) and a dynamic blocking ABS (DBA) have been proposed. All these algorithms require the staying tags to reply with their IDs to be recognized by the reader. However, the IDs of the staying tags are stored in the reader in the last identification round. The reader can verify the existence of these tags when identifying them. Thus, we propose an anti-collision algorithm with short reply for RFID tag identification (ACSR). In ACSR, each staying tag emits a short reply to indicate its continued existence. Therefore, the data amount transmitted by staying tags is reduced significantly. The identification rate of ACSR is analyzed in this paper. Finally, simulation and analysis results show that ACSR greatly outperforms ABS, SRB and DBA in terms of the identification rate and average amount of data transmitted by a tag.

We present a dynamic key generation method, KeyQ, for establishing shared secret keys in EPCglobal Generation 2 (Gen2) compliant systems. Widespread adoption of Gen2 technologies has increased the need for protecting communications in these systems. The highly constrained resources on Gen2 tags limit the usability of traditional key distribution techniques. Dynamic key generation provides a secure method to protect communications with limited key distribution requirements. Our KeyQ method dynamically generates fresh secret keys based on the Gen2 adaptive Q algorithm. We show that the KeyQ method generates fresh and unique secret keys that cannot be predicted with probability greater than 10-250 when the number of tags exceeds 100.

As RFID technology is being more widely adopted, it is fairly common to read mobile tags using RFID systems, such as packages on conveyer belt and unit loads on pallet jack or forklift truck. In RFID systems, multiple tags use a shared medium for communicating with a reader. It is quite possible that tags will exit the reading area without being read, which results in tag leaking. In this letter, a reliable tag anti-collision algorithm for mobile tags is proposed. It reliably estimates the expectation of the number of tags arriving during a time slot when new tags continually enter the reader's reading area and no tag leaves without being read. In addition, it gives priority to tags that arrived early among read cycles and applies the expectation of the number of tags arriving during a time slot to the determination of the number of slots in the initial inventory round of the next read cycle. Simulation results show that the reliability of the proposed algorithm is close to that of DFSA algorithm when the expectation of the number of tags entering the reading area during a time slot is a given, and is better than that of DFSA algorithm when the number of time slots in the initial inventory round of next read cycle is set to 1 assuming that the number of tags arriving during a time slot follows Poisson distribution.

Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular protocols to resolve tag collisions in RFID systems. In DFSA, it is widely known that the optimal performance is achieved when the frame size is equal to the number of tags. So, a reader dynamically adjusts the next frame size according to the current number of tags. Thus it is important to estimate the number of tags exactly. In this paper, we propose a novel tag estimation and identification method using litmus (test) slots for DFSA. We compare the performance of the proposed method with those of existing methods by analysis. We conduct simulations and show that our scheme improves the speed of tag identification.

Existing query tree protocols deal with RFID tags in a blind manner. They query tags in a fixed bit order based on the assumption that the tag ID numbers are uniformly distributed throughout the range of the entire ID space because readers have no prior knowledge of the tags. This paper attempts to distinguish RFID applications where readers are already aware of all tags used by the application. We propose a heuristic query tree (H-QT) protocol that uses heuristic to select effective bits from known tags for the best queries in a divide and conquer approach. The performance evaluation shows that the proposed protocol is superior to original query tree protocols because it significantly reduces the number of tag collisions and no tag response.

Channel errors may exist in Radio Frequency IDentification (RFID) systems due to low power backscattering of tags. These errors prevent the rapid identification of tags, and reducing this deterioration is an important issue. This paper presents performance analysis of various tag anti-collision algorithms and shows that the performances of RFID systems can be improved by applying a proposed robust algorithm in error-prone environments.

This letter proposes the Inference Algorithm through Effective Slot Allocation (ESA-IA). In ESA-IA, the tags which match the prefix of the reader's request-respond in the corresponding slot; the group of tags with an even number of 1's responds in slot 0, while the group with an odd number of 1's responds in slot 1. The proposed algorithm infers '00' and '11' if there are two collided bits in slot 0, while inferring '01' and '10' if there are two collided bits in slot 1. The ESA-IA decreases the time consumption for tag identification by reducing the overall number of queries.

To reduce RFID tag identification delay, we propose a novel Dynamic Splitting protocol (DS) which is an improvement of the Query tree protocol (QT). DS controls the number of branches of a tree dynamically. An improved performance of DS relative to QT is verified by analytical results and simulation studies.

In this paper we propose a novel RFID anti-collision technique that intelligently combines polling and random access schemes. These two fundamentally different medium access control protocols are coherently integrated in our design while functionally complementing each other. The polling mode is designed to enable fast collision-free identification for the tags that exist within reader's coverage across the sessions. In contrast, the random access mode attempts to read the tags uncovered by the polling mode. Our proposed technique is particularly suited for a class of RFID applications in which a stationary reader periodically attempts to identify the tags with slow mobility. Numerical results show that our proposed technique yields much faster identification time against the existing approaches under various operating conditions.

In this letter, we propose a new scheme for the tag structure of the EPCglobal Class-1 Generation-2 (EPC C1 Gen2) standard equipped with a channel encoding block and the corresponding decoding block in the receiver of the reader system. The channel coded tag is designed to fully accommodate the EPC C1 Gen2 standard. The use of the proposed channel encoding block increases the number of logic gates in the tag by no more than 5%. The proposed reader system is designed to be used in the mixed tag modes as well, where the channel coded tags and existing tags co-exist in the same inventory round. The performances of the proposed tags and the corresponding reader systems are also presented by comparing the number of EPC error frames and the tag identification time with those of the conventional tags and reader systems.

UHF radio frequency identification (RFID) has gathered significant interest in the field of long-distance automatic identification applications. Since UHF RFID shares the frequency band with other RFID and/or other wireless systems, it is important to determine how much interference can be applied without causing a significant degradation of anti-collision speed. In this paper, the permissible link quality for RFID anti-collision in a practical environment is discussed by considering an erroneous communication link, taking into account of bit encoding and the type of interference. We approach the quantification of permissible link quality experimentally along with protocol simulations and the mathematical analyses. An international standard protocol, employing frame slotted ALOHA, was used as the air protocol. For these investigations, the present authors developed a protocol simulator. The simulation results were compared with analytical values based on Poisson distribution. The investigation in the return (tag to reader) link, and the forward (reader to tag) link, were analyzed separately. As result of the protocol simulation, it is generally important to secure the Pulse Error Rate 10-4 or better in both return and forward links for the anti-collision of 64 or less tags. The quality of the return link may be relaxed when the application does not require fast anti-collision. The degradation of the forward link, on the other hand, may entail loss of important commands, resulting in extremely slow anti-collision. It is measured experimentally that the required link quality can be relaxed by up to 10 dB in the return links and by 5 dB in the forward link when the primary source of interference originates in the interfering readers.

Binary search tree and framed ALOHA algorithms are commonly adopted to solve the anti-collision problem in RFID systems. In this letter, the read efficiency of these two anti-collision algorithms is compared through computer simulations. Simulation results indicate the framed ALOHA algorithm requires less total read time than the binary search tree algorithm. The initial frame length strongly affects the uplink throughput for the framed ALOHA algorithm.

The collision of ID signals from a large number of co-located passive RFID tags is a serious problem; to realize a practical RFID systems we need an effective anti-collision algorithm. This letter presents an adaptive algorithm to minimize the total time slots and the number of rounds required for identifying the tags within the RFID reader's interrogation zone. The proposed algorithm is based on the framed ALOHA protocol, and the frame size is adaptively updated each round. Simulation results show that our proposed algorithm is more efficient than the conventional algorithms based on the framed ALOHA.