Censored Truncated Sequential Spectrum Sensing for Cognitive Radio Networks

Reliable spectrum sensing is a key functionality of a cognitive radio network. Cooperative spectrum sensing improves the detection reliability of a cognitive radio system but also increases the system energy consumption which is a critical factor particularly for low-power wireless technologies. A c...

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Published inIEEE journal on selected areas in communications Vol. 31; no. 3; pp. 364 - 378
Main Authors Maleki, S., Leus, G.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2013
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
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ISSN0733-8716
1558-0008
DOI10.1109/JSAC.2013.130304

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Abstract Reliable spectrum sensing is a key functionality of a cognitive radio network. Cooperative spectrum sensing improves the detection reliability of a cognitive radio system but also increases the system energy consumption which is a critical factor particularly for low-power wireless technologies. A censored truncated sequential spectrum sensing technique is considered as an energy-saving approach. To design the underlying sensing parameters, the maximum {average energy consumption per sensor} is minimized subject to a lower bounded global probability of detection and an upper bounded false alarm rate. This way both the interference to the primary user due to miss detection and the network throughput as a result of a low false alarm rate are controlled. {To solve this problem, it is assumed that the cognitive radios and fusion center are aware of their location and mutual channel properties.} We compare the performance of the proposed scheme with a fixed sample size censoring scheme under different scenarios and show that for low-power cognitive radios, censored truncated sequential sensing outperforms censoring. It is shown that as the sensing energy per sample of the cognitive radios increases, the energy efficiency of the censored truncated sequential approach grows significantly.
AbstractList Reliable spectrum sensing is a key functionality of a cognitive radio network. Cooperative spectrum sensing improves the detection reliability of a cognitive radio system but also increases the system energy consumption which is a critical factor particularly for low-power wireless technologies. A censored truncated sequential spectrum sensing technique is considered as an energy-saving approach. To design the underlying sensing parameters, the maximum {average energy consumption per sensor} is minimized subject to a lower bounded global probability of detection and an upper bounded false alarm rate. This way both the interference to the primary user due to miss detection and the network throughput as a result of a low false alarm rate are controlled. {To solve this problem, it is assumed that the cognitive radios and fusion center are aware of their location and mutual channel properties.} We compare the performance of the proposed scheme with a fixed sample size censoring scheme under different scenarios and show that for low-power cognitive radios, censored truncated sequential sensing outperforms censoring. It is shown that as the sensing energy per sample of the cognitive radios increases, the energy efficiency of the censored truncated sequential approach grows significantly.
Author Leus, G.
Maleki, S.
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StartPage 364
SubjectTerms Analytical models
censoring
Channels
Cognitive radio
cognitive radio networks
Design engineering
Detection
distributed spectrum sensing
Energy consumption
energy efficiency
False alarms
Interference
Networks
Optimization
Reliability
Sensors
sequential sensing
Studies
Title Censored Truncated Sequential Spectrum Sensing for Cognitive Radio Networks
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