Green Cooperative Cognitive Radio: A Multiobjective Optimization Paradigm

被引：18
|
作者：
Naeem, Muhammad [1 ,2 ]
Khwaja, Ahmed Shaharyar [3 ]
Anpalagan, Alagan [1 ]
Jaseemuddin, Muhammad [1 ]
机构：
[1] Ryerson Univ, Dept Elect & Comp Engn, WIreless Networks & COmmun Res Lab, Toronto, ON M5B 2K3, Canada
[2] COMSATS Inst Informat Technol, Wah Cantt 47040, Pakistan
[3] Ryerson Univ, WINCORE Lab, Toronto, ON M5B 2J1, Canada
来源：
IEEE SYSTEMS JOURNAL | 2016年 / 10卷 / 01期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Cooperative cognitive radio (CR); green wireless communication; ALLOCATION;
D O I：
10.1109/JSYST.2014.2301952
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we apply the cross-entropy optimization (CEO) to the problem of joint multiple relay assignment and source/relay power allocation in green cooperative cognitive radio (GCCR) networks. We use shared-band amplify-and-forward relaying for cooperative communication in this problem. The proposed joint multiple relay assignment and source/relay power allocation jointly performs relay assignment and power allocation in GCCR while optimizing two conflicting objectives: The first one is to maximize the total rate, and the second one is to minimize the greenhouse gas emissions in GCCR networks. This multiobjective optimization problem is a nonconvex combinatorial optimization problem and is NP-hard. We use a Monte-Carlo-based CEO algorithm to solve this nonconvex problem. The CEO has a simplistic model, and its robustness in avoiding local minima/maxima makes it a suitable candidate for solving complex combinatorial optimization problems. We present simulation results that verify the effectiveness of the proposed CEO method for joint multiple relay assignment and source/relay power allocation.
引用
收藏
页码：240 / 250
页数：11
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