Resource optimisation using bandwidth-power product for multiple-input multiple-output orthogonal frequency-division multiplexing access system in cognitive radio networks

This study investigates resource allocation problems for a point-to-point multi-carrier multiple-input multiple-output cognitive radio network. Different from conventional resource optimisation problems, a joint power and bandwidth resource optimisation framework using the novel optimisation metric,...

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Bibliographic Details
Published in:	IET communications Vol. 9; no. 14; pp. 1710 - 1720
Main Authors:	Chen, Bo, Zhao, Minjian, Zhang, Lei, Lei, Ming
Format:	Journal Article
Language:	English
Published:	The Institution of Engineering and Technology 22.09.2015
Subjects:	Algorithms Allocations bandwidth‐power product Channels Cognitive radio frequency division multiple access Gauss‐Newton method integer programming joint power and bandwidth resource optimisation framework Lagrange‐duality theory MIMO communication mixed‐integer programming problem multiple‐input multiple‐output orthogonal frequency‐division multiplexing access system Networks optimal source precoding matrix optimisation metric Optimization point‐to‐point multi‐carrier multiple‐input multiple‐output cognitive radio network primary users project‐channel singular value decomposition resource allocation resource allocation problems Singular value decomposition SVD User satisfaction SVD primary users frequency division multiple access integer programming mixed-integer programming problem point-to-point multi-carrier multiple-input multiple-output cognitive radio network resource allocation problems Lagrange-duality theory Gauss-Newton method joint power and bandwidth resource optimisation framework resource allocation cognitive radio project-channel singular value decomposition optimisation metric bandwidth-power product optimal source precoding matrix MIMO communication singular value decomposition multiple-input multiple-output orthogonal frequency-division multiplexing access system
ISSN:	1751-8628, 1751-8636
Online Access:	Get full text
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