A High-Dimensional Collided Tag Quantity Estimation Method for Multi-Antenna RFID Systems
| Autor: | Wei Deng, Wenjiang Pei, Zhe Li, Yili Xia, Pu Rui |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
DBSCAN
Backscatter Computer science business.industry Estimator 020206 networking & telecommunications Context (language use) 02 engineering and technology Antenna diversity Computer Science Applications Signal-to-noise ratio Modeling and Simulation 0202 electrical engineering electronic engineering information engineering Radio-frequency identification Electrical and Electronic Engineering business Cluster analysis Throughput (business) Algorithm Computer Science::Information Theory |
| Zdroj: | IEEE Communications Letters. 25:132-136 |
| ISSN: | 2373-7891 1089-7798 |
| DOI: | 10.1109/lcomm.2020.3024688 |
| Popis: | Accurate tag quantity estimation is a prerequisite to maximize the throughput of radio frequency identification (RFID) systems. Previous estimators, mainly designed for single-antenna RFID systems, often suffer from performance degradation in low signal-to-noise-ratio (SNR) regimes, making them inappropriate for multi-antenna RFID systems where received tag signals are likely to overlap. In this regard, a high-dimensional tag quantity estimator is proposed in the multi-antenna context by exploiting the spatial diversity at receive antennas. We first show that the collided tag signals can be rearranged as high-dimensional vectors, whereby the tag quantity estimation problem can be modeled as a high-dimensional data clustering one. We next prove that when the SNR on each backscattering subchannel is greater than 3 dB, the distance incrementation between clusters offered by the modeling advantage benefits their separation. This finding encourages us to integrate the density-based spatial clustering of applications with noise (DBSCAN) algorithm with this high-dimensional space for tag quantity estimation, and its superiority over several existing approaches are supported by both synthetic and real-world case studies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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