A robust energy efficiency power allocation algorithm in cognitive radio networks

• Published in: China communications Vol. 15; no. 10; pp. 150 - 158
• Main Authors: Zhou, Mingyue, Zhao, Xiaohui
• Format: Journal Article
• Language: English
• Published: China Institute of Communications 01.10.2018; College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China; Key Laboratory of Information Science, College of Communication Engineering, Jilin University, Changchun 130012, China%Key Laboratory of Information Science, College of Communication Engineering, Jilin University, Changchun 130012, China
• Subjects: cognitive radio; Energy efficiency; Interference; Optimization; power allocation; Resource management; Robustness; Signal to noise ratio; spectrum sharing; Uncertainty; power allocation; cognitive radio; spectrum sharing
• ISSN: 1673-5447
• DOI: 10.1109/CC.2018.8485477

In order to solve the problem that traditional energy efficiency power allocation algorithms usually require the assumption of constant or perfect channel state information in cognitive radio networks (CRNs), which may lead to performance degradation in real systems with disturbances or uncertainties, we propose a robust energy efficiency power allocation algorithm for underlay cognitive radio (CR) systems with channel uncertainty in consideration of interference power threshold constraint and minimum target SINR requirement constraint. The ellipsoid sets are used to describe the channel uncertainty, and a constrained fractional programming for the allocation is transformed to a convex optimization problem by worst-case optimization approach. A simplified version of robust energy efficiency scheme by a substitutional constraint having lower complexity is presented. Simulation results show that our proposed scheme can provide higher energy efficiency compared with capacity maximization algorithm and guarantee the signal to interference plus noise ratio (SINR) requirement of each cognitive user under channel uncertainty.