Compressed RSS Measurement for Communication and Sensing in the Internet of Things
Joint Authors
Li, Wenzhong
Lu, Sanglu
Chen, Bing
Zhao, Yanchao
Wu, Jie
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-07
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
The receiving signal strength (RSS) is crucial for the Internet of Things (IoT), as it is the key foundation for communication resource allocation, localization, interference management, sensing, and so on.
Aside from its significance, the measurement process could be tedious, time consuming, inaccurate, and involving human operations.
The state-of-the-art works usually applied the fashion of “measure a few, predict many,” which use measurement calibrated models to generate the RSS for the whole networks.
However, this kind of methods still cannot provide accurate results in a short duration with low measurement cost.
In addition, they also require careful scheduling of the measurement which is vulnerable to measurement conflict.
In this paper, we propose a compressive sensing- (CS-) based RSS measurement solution, which is conflict-tolerant, time-efficient, and accuracy-guaranteed without any model-calibrate operation.
The CS-based solution takes advantage of compressive sensing theory to enable simultaneous measurement in the same channel, which reduces the time cost to the level of O ( log N ) (where N is the network size) and works well for sparse networks.
Extensive experiments based on real data trace are conducted to show the efficiency of the proposed solutions.
American Psychological Association (APA)
Zhao, Yanchao& Li, Wenzhong& Wu, Jie& Lu, Sanglu& Chen, Bing. 2017. Compressed RSS Measurement for Communication and Sensing in the Internet of Things. Wireless Communications and Mobile Computing،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1206030
Modern Language Association (MLA)
Zhao, Yanchao…[et al.]. Compressed RSS Measurement for Communication and Sensing in the Internet of Things. Wireless Communications and Mobile Computing No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1206030
American Medical Association (AMA)
Zhao, Yanchao& Li, Wenzhong& Wu, Jie& Lu, Sanglu& Chen, Bing. Compressed RSS Measurement for Communication and Sensing in the Internet of Things. Wireless Communications and Mobile Computing. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1206030
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206030