Wireless Coexistence and Spectrum Sensing in Industrial Internet of Things: An Experimental Study
Author(s) -
Jean M. Winter,
Ivan Müller,
Gloria Soatti,
Stefano Savazzi,
Monica Nicoli,
Leandro Buss Becker,
João C. Netto,
Carlos Eduardo Pereira
Publication year - 2015
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2015/627083
Subject(s) - computer science , industrial internet , cognitive radio , reliability (semiconductor) , wireless , wireless sensor network , interference (communication) , wireless network , computer network , the internet , heterogeneous network , radio resource management , channel (broadcasting) , resource (disambiguation) , telecommunications , internet of things , computer security , power (physics) , physics , quantum mechanics , world wide web
The adoption of dense wireless sensor networks in industrial plants is mandatorily paired with the development of methods and tools for connectivity prediction. These are needed to certify the quality (or reliability) of the network information flow in industrial scenarios which are typically characterized by harsh propagation conditions. Connectivity prediction must account for the possible coexistence of heterogeneous radio-access technologies, as part of the Industrial Internet of Things (IIoT) paradigm, and easily allow postlayout validation steps. The goal of this paper is to provide a practical evaluation of relevant coexistence problems that may occur between industrial networks employing standards such as WirelessHART IEC 62591, IEEE 802.15.4, and IEEE 802.11. A number of coexistence scenarios are experimentally tested using different radio platforms. For each case, experimental results are analyzed to assess tolerable interference levels and sensitivity thresholds for different configurations of channel overlapping. Finally, the problem of over-the-air spectrum sensing is investigated in real scenarios with heterogeneous industrial networks to enable a cognitive resource allocation that avoids intolerable interference conditions.
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