An efficient sub-frame based tag identification algorithm for UHF RFID systems

Su, Jian; Sheng, Zhengguo; Hong, Danfeng; Leung, Victor C. M.

doi:10.1109/icc.2016.7511360

Cited by 18 publications

(29 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, we propose an improved DFSA version that uses the estimate tag quantity in its estimate step. The resulting algorithm, which is based on “Query” Q‐selection to choose the next frame length, are summarized in Figure and given as follows: Setting the initial frame length L 1 = 128 slots and sending the request command ( Q 1 = 7 that correspond to a frame length of 128) to tags asking for their information. All the tags randomly select one slot from 2 0 to

2^{Q_{i}}

to respond and finish the identification of one frame. Count the read result of this frame <( c 0 ; c 1 ; c k ) i = 1 > and use the result to estimate the tag number using our estimation method. Estimate the number of the tag

{\overset{n}{true}}_{i}

, i = 1 using our proposed estimate method. Sends a request

Q_{i} = l o g_{2} false({\overset{n}{true}}_{i - 1} - c_{1 false(i - 1 false)} false)

that correspond to

L_{i} = {\overset{n}{true}}_{i - 1} - c_{1 false(i - 1 false)}

slots, i = 2. All the tags randomly select a new slot from L 2 slots. The reader iterates the operations {2,3,and 4} and sends at each end of frame a request that indicate the length of the next frame.…”

Section: Simulation Resultsmentioning

confidence: 99%

A cooperative Bayesian and lower bound estimation in dynamic framed slotted ALOHA algorithm for RFID systems

Benssalah

Djeddou

Dahou

et al. 2018

Int J Communication

View full text Add to dashboard Cite

A novel estimation scheme that combines Bayesian and lower bound estimating radio frequency identification tag population size is proposed. The developed methodology is based on the fusion between the Bayesian and lower bound estimating techniques. It turns out that the fusion rule is built up thanks to an existing linear relationship between the cited techniques. Simulation resultsshow that the developed technique significantly improves the accuracy of the estimating tag quantity and presents less estimation error. Also, the resulting advanced dynamic framed slotted ALOHA protocol considerably improves the performance and efficiency of the radio frequency identification anti-collision compared with the most recent protocols using others estimating methods. KEYWORDSBayesian estimation, lower bound, RFID, slotted ALOHA INTRODUCTIONRadio frequency identification (RFID) technology is becoming an integral part in a wide spectrum of applications, such as access control, distribution, medicine, and RFID-embedded cards. However, despite the significant increasing of the density of available tags in the readers' interrogation zones, the tag collision problem remains a serious issue that must be addressed seriously before any deployment. The collision problem occurs when simultaneous tags share the same communication channel with the interrogating reader. As a result, the reader will not be able to get the correct identity from each tag. Recently, several state-of-the-art anti-collision tag identification algorithms have been proposed in the literature to mitigate the low tag identification efficiency and performance.The anti-collision algorithm can be divided into 2 main categories. 1 The first category concerns the anti-collision techniques that are processed in medium access control (MAC) layer. In this category, most of the RFID reader uses dynamic framed slotted ALOHA (DFSA)-based probabilistic algorithms. 2-7 The DFSA protocols dynamically adjust the frame size in the successive rounds according to the estimating tags quantity. In fact, DFSA anti-collision protocols can be divided into 2 key parts. The first one deals on how to estimate the tag quantity during an inventory process. The second part focuses on how to dynamically adjust frame size, according to the estimated number of tags, to achieve maximum throughput. Knowing that, the tag quantity to be read is usually unknown, and the maximum throughput of the system is achieved when the frame length is equal to the number of tags of the system. 8 Therefore, it is utmost important to use an estimation method of high accuracy in order to not affect the reading performance of DFSA algorithms.In this context, numerous methods have been proposed in the literature. Among conventional methods (process the problem in MAC layer), the basic ones are idle slot estimate, 9 lower bound estimate, 10 and Schoute estimate. 11 So far, Int J Commun Syst. 2018;31:e3723.wileyonlinelibrary.com/journal/dac

show abstract

2^{Q_{i}}

{\overset{n}{true}}_{i}

, i = 1 using our proposed estimate method. Sends a request

Q_{i} = l o g_{2} false({\overset{n}{true}}_{i - 1} - c_{1 false(i - 1 false)} false)

that correspond to

L_{i} = {\overset{n}{true}}_{i - 1} - c_{1 false(i - 1 false)}

Section: Simulation Resultsmentioning

confidence: 99%

A cooperative Bayesian and lower bound estimation in dynamic framed slotted ALOHA algorithm for RFID systems

Benssalah

Djeddou

Dahou

et al. 2018

Int J Communication

View full text Add to dashboard Cite

show abstract

“…To achieve the robust performance, the slotby-slot (SbS) version of ILCM has been presented in [27]. The sub-frame based algorithms [28], [29] recently have been proposed to overcome the accumulated estimation error. Specifically, the tag cardinality is estimated based on linear relation between empty and collision slot statistically counted in a sub-frame [28].…”

Section: Probabilistic Algorithmsmentioning

confidence: 99%

“…The sub-frame based algorithms [28], [29] recently have been proposed to overcome the accumulated estimation error. Specifically, the tag cardinality is estimated based on linear relation between empty and collision slot statistically counted in a sub-frame [28]. Since the computational complexity of the estimation is reduced, the energy efficiency of SUBF-DFSA can be improved compared to the estimation methods with high complexity.…”

Section: Probabilistic Algorithmsmentioning

confidence: 99%

“…The setting of sub-frame size should also be seriously considered. Referring to our previous works [28], [29], we recommend sub-frame size as listed in the Tab. 1.…”

Section: Cardinality Estimationmentioning

confidence: 99%

“…As concluded in the previous works [27], [28], the slot efficiency is ineffective to evaluate the actual performance of anti-collision approaches because it assumes the time interval of different types of slots are equal. In addition, the number of different types of time slots varies from algorithm to algorithm.…”

Section: The Number Of Different Types Of Slotsmentioning

confidence: 99%

See 2 more Smart Citations

A Partitioning Approach to RFID Identification

Liu

Sheng

et al. 2020

IEEE/ACM Trans. Networking

Self Cite

View full text Add to dashboard Cite

Radio-frequency identification (RFID) is a major enabler of Internet of Things (IoT), and has been widely applied in tag-intensive environments. Tag collision arbitration is considered as a crucial issue of such RFID system. To enhance the reading performance of RFID, numerous anti-collision algorithms have been presented in previous literatures. However, most of them suffer from the slot efficiency bottleneck of 0.368. In this paper, we revisit the performance of tag identification in Aloha-based RFID anti-collision approaches from the perspective of time efficiency. Based on comprehensive reviews and analysis of the existing algorithms, a novel partitioning approach is proposed to maximize identification performance in framed slotted Aloha based UHF RFID systems. In the proposed approach, the tag set is divided into many groups which only contains a few tags, and then each group is identified in sequence. Benefiting from the optimal partition, the proposed algorithm can achieve a significant performance improvement. Simulation results supplemented by prototyping tests show that the proposed solution achieves an asymptotical slot efficiency up to 0.4348, outperforming the existing UHF RFID solutions.

show abstract

A Method to Improve Identification Performance of UHF RFID Systems

2020

Communications in Computer and Information Science

View full text Add to dashboard Cite

An efficient sub-frame based tag identification algorithm for UHF RFID systems

Cited by 18 publications

References 10 publications

A cooperative Bayesian and lower bound estimation in dynamic framed slotted ALOHA algorithm for RFID systems

A cooperative Bayesian and lower bound estimation in dynamic framed slotted ALOHA algorithm for RFID systems

A Partitioning Approach to RFID Identification

A Method to Improve Identification Performance of UHF RFID Systems

Contact Info

Product

Resources

About