Evidence map›Paper›PMID 27023560›Full record

ArticleSensors (Basel, Switzerland)2016

LS Channel Estimation and Signal Separation for UHF RFID Tag Collision Recovery on the Physical Layer.

Hanjun Duan, Haifeng Wu, Yu Zeng, Yuebin Chen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hanjun DuanSchool of Electrical and Information Technology, Yunnan University of Nationalities, 650500 Kunming, China. hansonduan@foxmail.com.
Haifeng WuSchool of Electrical and Information Technology, Yunnan University of Nationalities, 650500 Kunming, China. wuhaifeng@ynni.edu.cn.
Yu ZengSchool of Electrical and Information Technology, Yunnan University of Nationalities, 650500 Kunming, China. yv.zeng@gmail.com.
Yuebin ChenSchool of Electrical and Information Technology, Yunnan University of Nationalities, 650500 Kunming, China. cybuestc@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In a passive ultra-high frequency (UHF) radio-frequency identification (RFID) system, tag collision is generally resolved on a medium access control (MAC) layer. However, some of collided tag signals could be recovered on a physical (PHY) layer and, thus, enhance the identification efficiency of the RFID system. For the recovery on the PHY layer, channel estimation is a critical issue. Good channel estimation will help to recover the collided signals. Existing channel estimates work well for two collided tags. When the number of collided tags is beyond two, however, the existing estimates have more estimation errors. In this paper, we propose a novel channel estimate for the UHF RFID system. It adopts an orthogonal matrix based on the information of preambles which is known for a reader and applies a minimum-mean-square-error (MMSE) criterion to estimate channels. From the estimated channel, we could accurately separate the collided signals and recover them. By means of numerical results, we show that the proposed estimate has lower estimation errors and higher separation efficiency than the existing estimates.

Indexed as

channel estimationleast-squareRFIDsignal separationtag collision

Identifiers

PMID27023560
PMCPMC4850956

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.