Mendeley
TY  _  JOUR
ID  -  139606191316447990
TI  -  Lifetime Maximization by Dynamic Threshold and Sensor Selection in Multi-channel Cognitive Sensor Network
JO  -  Journal of Information Systems and Telecommunication (JIST) 
JA  -  ES
LA  -  en
SN  -  2322-1437
AU  -  Bagheri Asma
AU  -  Ebrahimzadeh Ataollah
AU  -  najimi maryam
AD  -  Esfarayen University of Technology
AD  -  BUT
AD  -  Department of Electrical and Computer Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran
Y1  -  2018
PY  -  2018
VL  -  20
IS  -  5
SP  -  225
EP  -  235
KW  -  Cognitive sensor network
KW  -   Detection probability
KW  -   False alarm probability
KW  -   Lifetime
KW  -   Multi-channel cooperative spectrum sensing
DO  -  
N2  -  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 complexity of the problem it is proposed the Bisection method 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.
UR  - rimag.ir/en/Article/15062
L1  - rimag.ir/en/Article/Download/15062
ER  -  
