Open AccessResource optimisation using bandwidth‐power product for multiple‐input multiple‐output orthogonal frequency‐division multiplexing access system in cognitive radio networks
Author(s) -
Chen Bo,
Zhao Minjian,
Zhang Lei,
Lei Ming
Publication year - 2015
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2014.1108
Subject(s) - cognitive radio , computer science , bandwidth (computing) , orthogonal frequency division multiple access , orthogonal frequency division multiplexing , multiplexing , transmitter power output , time division multiplexing , channel access method , telecommunications , computer network , electronic engineering , transmitter , wireless , engineering , channel (broadcasting)
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, namely bandwidth‐power product, is developed. Besides, rate requirement of the secondary system is satisfied, and the interferences introduced to the primary users (PUs) are below threshold of tolerance. The optimal source precoding matrix is designed and two methods, namely the project‐channel singular value decomposition (SVD) and direct‐channel SVD methods, are applied to satisfy interference power constraints for PUs. Then the unified power and channel allocation problem is derived and found to be a mixed‐integer programming problem. Hence, a sub‐optimal and tractable algorithm with low complexity is proposed. The innovative idea is to determine the channel resource budget by selecting the best channels, where the criterion for evaluating the quality of channel is detailed discussed. Then the power optimisation subproblem and channel allocation subproblem can be performed independently using the Lagrange‐duality theory and Gauss–Newton method, respectively. The simulation results show significant improvement in spectral efficiency by using this framework compared to classical power optimisation framework using the waterfilling scheme.