A Dual-Response Collision Tree Anti-Collision Protocol for Large-Scale RFID Tags Identification

This paper proposes the Dual-Response Collision Tree Anti-Collision Protocol (DRCT), redesigning tree-based approaches to address performance degradation in large-scale RFID identification. DRCT achieves optimization through a systemic design based on three key integrated mechanisms: Firstly, a novel Tag Grouping mechanism, fundamentally distinct from collision-bit-dependent methods, uses magnitude comparison against a reader-defined dynamic prefix (preStr). This eliminates the need to analyze the immediate collision for partitioning, enabling immediate parallel R0/R1-cycle processing readiness. Secondly, to effectively manage the identification process under this novel partitioning scheme, DRCT introduces a crucial Localized Search Control mechanism. This relies on tag-side counters (seDepth) which are conditionally updated by incrementing only when a tag is involved in an R1-cycle (<preStr) collision that requires further resolution. It accurately filters tag participation to the relevant branch, and minimizes inherent redundancy. Thirdly, building upon this controlled tag participation, highly efficient Low-Bit Collision Detection (4-bit Check, 2-bit Answer) maximizes the protocol’s efficiency potential by drastically reducing communication overhead per cycle for rapid slot state assessment. The synergy between these mechanisms allows DRCT to achieve superior performance. Theoretical analysis and experimental results demonstrate DRCT’s significant advantages over state-of-the-art tree-based protocols, achieving 84.8% channel utilization, at least 27.75% energy reduction, and 14.0% faster identification, while substantially enhancing stability, evidenced by an approximately 21.5% lower average standard deviation.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-06-17
DOI
https://doi.org/10.1109/jiot.2025.3580419
Citations
1
Primary Topic
RFID technology advancements
Type
article
Field-Weighted Citation Impact
1.14

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article

A Dual-Response Collision Tree Anti-Collision Protocol for Large-Scale RFID Tags Identification

Zhong Du, Xiaolin Jia, Hongquan Zhou, Yajun Gu
1 citations
IEEE Internet of Things Journal
RFID technology advancements
1.14
article

A Dual-Response Collision Tree Anti-Collision Protocol for Large-Scale RFID Tags Identification

Zhong Du, Xiaolin Jia, Hongquan Zhou, Yajun Gu
article en
1 citations

Abstract

This paper proposes the Dual-Response Collision Tree Anti-Collision Protocol (DRCT), redesigning tree-based approaches to address performance degradation in large-scale RFID identification. DRCT achieves optimization through a systemic design based on three key integrated mechanisms: Firstly, a novel Tag Grouping mechanism, fundamentally distinct from collision-bit-dependent methods, uses magnitude comparison against a reader-defined dynamic prefix (preStr). This eliminates the need to analyze the immediate collision for partitioning, enabling immediate parallel R0/R1-cycle processing readiness. Secondly, to effectively manage the identification process under this novel partitioning scheme, DRCT introduces a crucial Localized Search Control mechanism. This relies on tag-side counters (seDepth) which are conditionally updated by incrementing only when a tag is involved in an R1-cycle (<preStr) collision that requires further resolution. It accurately filters tag participation to the relevant branch, and minimizes inherent redundancy. Thirdly, building upon this controlled tag participation, highly efficient Low-Bit Collision Detection (4-bit Check, 2-bit Answer) maximizes the protocol’s efficiency potential by drastically reducing communication overhead per cycle for rapid slot state assessment. The synergy between these mechanisms allows DRCT to achieve superior performance. Theoretical analysis and experimental results demonstrate DRCT’s significant advantages over state-of-the-art tree-based protocols, achieving 84.8% channel utilization, at least 27.75% energy reduction, and 14.0% faster identification, while substantially enhancing stability, evidenced by an approximately 21.5% lower average standard deviation.

IEEE Internet of Things JournalVol. 12(18)
Southwest University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 19%
RFID technology advancements
1.14
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A Dual-Response Collision Tree Anti-Collision Protocol for Large-Scale RFID Tags Identification — Zhong Du, Xiaolin Jia, et al. · IEEE Internet of Things Journal (2025) | TGRS Research Map | TGRS