Open AccessSensing Time Optimisation and Sensor Selection in Multi‐channel Multi‐antenna Wireless Cognitive Sensor Networks
Author(s) -
Najimi Maryam
Publication year - 2018
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2017.0299
Subject(s) - cognitive radio , wireless sensor network , computer science , channel (broadcasting) , energy (signal processing) , antenna (radio) , wireless , energy consumption , false alarm , real time computing , efficient energy use , electronic engineering , computer network , telecommunications , engineering , electrical engineering , artificial intelligence , mathematics , statistics
Energy efficiency of cooperative spectrum sensing is a critical issue in wireless cognitive sensor networks (CSNs). However, sensor nodes consume high energy to support cognitive radio (CR) functionalities such as channel sensing. In this study, the energy‐efficient cooperative spectrum sensing in multi‐channel multi‐antenna CSNs is investigated. First, a multi‐channel CSN is considered to obtain sensing sensors and sensing time for each band in a CR system. The criteria is to minimise energy consumption of cooperative spectrum sensing under the global probabilities of detection and false alarm constraints. The authors employ a convex optimisation method to obtain optimal sensing time and sensing nodes for each band. Next, their analysis is extended into multi‐antenna sensors, which is a promising solution instead of using more sensors. In multi‐antenna cooperative spectrum sensing, diversity helps sensors behave virtually the same as multi‐sensors systems. Then, the problem of sensor selection and also setting the sensing time for each band is solved based on the convex optimisation framework. Simulation results highlight that in their proposed algorithms a significant energy is saved compared with the baseline methods with equal sensing time in all bands.