Guest Editorial: Networks in Harsh Environments

Networks deployed in harsh environments, such as high-speed trains, subways, deserts, trenches, forests, and underground mining, should be specially constructed to withstand extreme conditions such as high or low temperatures, corrosive humidity, extreme weather or excessive dust and dirt. Such appl...

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Bibliographic Details
Published inIEEE network Vol. 36; no. 4; pp. 8 - 9
Main Authors Liang, Qilian, Durrani, Tariq S., Liang, Jing, Wang, Xin, Koh, Jinhwan, Xiao, Shu
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Artificial intelligence
Channel coding
Doppler effect
Edge computing
Environmental factors
Fiber optics
High speed rail
Low temperature
MIMO communication
Network latency
Network reliability
Optical communication
Power consumption
Quality of service
Quality of service architectures
Reliability aspects
Satellite networks
Signal processing
Signal to noise ratio
Special issues and sections
Subway construction
Subways
Telecommunication network management
Telecommunication network performance
Telecommunication network reliability
Telecommunication services
Underground construction
Underground mining
Wireless networks
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Summary:Networks deployed in harsh environments, such as high-speed trains, subways, deserts, trenches, forests, and underground mining, should be specially constructed to withstand extreme conditions such as high or low temperatures, corrosive humidity, extreme weather or excessive dust and dirt. Such applications require specially designed wireless networks, sensor networks, fiber optic networks, or satellite networks that can perform under extreme conditions and meet the quality of service (QoS), security, and reliability requirement. Quite often, networks in harsh environments have extremely low signal-to-noise ratio (SNR), high Doppler shift, and long latency, and often consumes more power and energy. Bandwidth limitation in harsh environments requires spectrum-efficient communications. The current state -of-the-art technologies such as edge computing, massive multiple-input multiple-output (MIMO), advanced modulation and channel coding, artificial intelligence, and signal processing provide different venues to explore this challenging area.
ISSN:0890-8044
1558-156X
DOI:10.1109/MNET.2022.9919785