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

页码：240 / 250

页数：11

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