Open AccessEnergy efficient collaborative spectrum sensing with clustering of secondary users in cognitive radio networks
Author(s) -
Sharma Girraj,
Sharma Ritu
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5109
Subject(s) - cognitive radio , computer science , overhead (engineering) , transmission (telecommunications) , cluster analysis , fusion center , fusion rules , energy (signal processing) , power (physics) , wireless , real time computing , electronic engineering , telecommunications , engineering , mathematics , artificial intelligence , statistics , image (mathematics) , image fusion , operating system , physics , quantum mechanics
Collaborative sensing also known as cooperative spectrum sensing (CSS) is an efficient spectrum sensing technique to improve the sensing accuracy in cognitive radio (CR). However, it brings extra collaborative sensing overhead due to mutual exchange of large information among CR users. In CSS, the number of cooperative users, fusion rule, transmission power and sensing time affects the energy efficiency (EE) of the CSS. In this study, a cluster‐based CSS is proposed with four fusion rules. Optimised fusion rule is determined that maximises the EE. For the proposed CSS, joint optimal sensing time and transmission power of energy efficient CSS is determined. The joint optimisation design problem is formulated as function of sensing time and transmission power subjected to primary user protection constraints. An iterative algorithm is proposed to determine joint optimal sensing time and transmission power that maximises the EE of CSS. Results show that EE is maximum for AND–OR fusion at sensing duration 2.3 ms and transmission power 1.11 W at SNR = −20 dB. Maximum EE at optimal point is = 3.735 Mbits/Hz/J.