当前位置: X-MOL 学术IEEE Wirel. Commun. Lett. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An Efficient Information Sampling Method for Multi-Category RFID Systems
IEEE Wireless Communications Letters ( IF 6.3 ) Pub Date : 2021-06-23 , DOI: 10.1109/lwc.2021.3091896
Chu Chu , Jianyu Niu , Hui Ma , Jian Su , Rui Xu , Guangjun Wen

In Radio Frequency Identification (RFID) applications, multiple tags may be deployed on the same object or area for security or precision purposes. These tags carry similar information and so can be grouped into a category. To collect such information, most existing works have to query all tags in each category, which is time-consuming. However, sampling a subset of tags from each category is sufficient. In this letter, we propose a new solution called arithmetic coding based sampling (ACS) protocol. Specifically, we construct a sparse vector to sample only a subset of tags from each category, which can not only avoid repetitive information collection but also reduce interference from unsampled tags. Moreover, we compress the sparse vector through arithmetic coding, which significantly reduces its transmission time. Both theoretical analysis and simulation results demonstrate that ACS outperforms existing solutions in time efficiency.

中文翻译:

一种多类别RFID系统的高效信息采样方法

在射频识别 (RFID) 应用中,出于安全或精确目的,可以在同一对象或区域上部署多个标签。这些标签携带相似的信息,因此可以归入一个类别。为了收集这些信息,现有的大多数作品都必须查询每个类别中的所有标签,这非常耗时。但是,从每个类别中采样一个标签子集就足够了。在这封信中,我们提出了一种称为基于算术编码的采样 (ACS) 协议的新解决方案。具体来说,我们构造了一个稀疏向量来仅对每个类别的标签子集进行采样,这不仅可以避免重复信息收集,还可以减少未采样标签的干扰。此外,我们通过算术编码压缩稀疏向量,这显着减少了其传输时间。
更新日期:2021-06-23
down
wechat
bug