DocumentCode
1754834
Title
Optimal power allocation for green cognitive radio: fractional programming approach
Author
Naeem, M. ; Illanko, K. ; Karmokar, A. ; Anpalagan, Alagan ; Jaseemuddin, M.
Author_Institution
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
Volume
7
Issue
12
fYear
2013
fDate
Aug. 13 2013
Firstpage
1279
Lastpage
1286
Abstract
In this study, the problem of determining the power allocation that maximises the energy efficiency of cognitive radio network is investigated as a constrained fractional programming problem. The energy-efficient fractional objective is defined in terms of bits per Joule per Hertz. The proposed constrained fractional programming problem is a non-linear non-convex optimisation problem. The authors first transform the energy-efficient maximisation problem into a parametric optimisation problem and then propose an iterative power allocation algorithm that guarantees ε-optimal solution. A proof of convergence is also given for the ε-optimal algorithm. The proposed ε-optimal algorithm provide a practical solution for power allocation in energy-efficient cognitive radio networks. In simulation results, the effect of different system parameters (interference threshold level, number of primary users and number of secondary users) on the performance of the proposed algorithms are investigated.
Keywords
cognitive radio; concave programming; environmental factors; iterative methods; nonlinear programming; ε-optimal solution; constrained fractional programming problem; energy-efficient cognitive radio networks; energy-efficient fractional objective; energy-efficient maximisation problem; green cognitive radio; interference threshold level; iterative power allocation algorithm; nonlinear nonconvex optimisation problem; optimal power allocation; parametric optimisation problem; primary users; secondary users;
fLanguage
English
Journal_Title
Communications, IET
Publisher
iet
ISSN
1751-8628
Type
jour
DOI
10.1049/iet-com.2012.0604
Filename
6583146
Link To Document