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Title

Lifetime Maximization by Dynamic Threshold and Sensor in Multi-Channel Cognitive Sensor Network

Year: 1396
COI: JR_JIST-5-4_007
Language: EnglishView: 170
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Authors

Asma Bagheri - Faculty of Electrical and Computer Engineering, Babol University of Technology, Babol, Iran
Ataollah Ebrahimzadeh - Faculty of Electrical and Computer Engineering, Babol University of Technology, Babol, Iran
Maryam Najimi - Faculty of Electrical Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran

Abstract:

The tiny and low-cost sensors cannot simultaneously sense more than one channel since they do not have high-speed Analog-to-Digital-Convertors (ADCs) and high-power batteries. It is a critical problem when they are used for multi-channel sensing in cognitive sensor networks (CSNs). One solution for this problem is that the sensors sense various channels at different sensing periods. Due to the energy limitation in these scenarios, the lifetime maximization will become an important issue. In this paper, maximizing the lifetime of a CSN is investigated by selecting both the cooperative sensors and their detector threshold, such that the desired detection performance constraints are satisfied. This is a NP-complete problem, and obtaining the optimum solution needs exhaustive search with exponential complexity order. Here we have proposed two convex-based optimization algorithms with low order of complexity. First algorithm applies the known instantaneous Signal-to-Noise-Ratio (SNR) and obtains the proper detector thresholds by solving an equation for every channel. Investigation the effect of detector thresholds on the energy consumption, the false alarm probability and the detection probability shows that we can minimize the detector thresholds such that the detection constraints are met. In the second algorithm in order to reduce the needed time for obtaining answers, the Bisection method is proposed for determining detector thresholds. Because knowing the instantaneous SNR is difficult, we have investigated the performance of the second algorithm by average value of SNR. Simulation results show that the proposed algorithms improve the performance of the network in case of lifetime and energy consumption.

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Paper COI Code

This Paper COI Code is JR_JIST-5-4_007. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/792089/

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If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Bagheri, Asma and Ebrahimzadeh, Ataollah and Najimi, Maryam,1396,Lifetime Maximization by Dynamic Threshold and Sensor in Multi-Channel Cognitive Sensor Network,https://civilica.com/doc/792089

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Type of center: دانشگاه دولتی
Paper count: 6,134
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