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Wireless Communications and Mobile Computing
Volume 2018, Article ID 1327030, 16 pages
https://doi.org/10.1155/2018/1327030
Research Article

Resource Allocation for Green Cognitive Radios: Energy Efficiency Maximization

Guangxi Power Grid Co., Power Grid Electric Power Research Institute, Nanning, China

Correspondence should be addressed to Wenqian Jiang; moc.621@yksqqwj

Received 20 March 2018; Revised 26 April 2018; Accepted 10 May 2018; Published 5 July 2018

Academic Editor: Zheng Chu

Copyright © 2018 Zhou Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Green cognitive radios are promising in future wireless communications due to high energy efficiency. Energy efficiency maximization problems are formulated in delay-insensitive green cognitive radio and delay-sensitive green cognitive radio. The optimal resource allocation strategies for delay-insensitive green cognitive radio and delay-sensitive green cognitive radio are designed to maximize the energy efficiency of the secondary user. The peak interference power and the average/peak transmit power constraints are considered. Two algorithms based on the proposed resource allocation strategies are proposed to solve the formulated problems. Simulation results show that the maximum energy efficiency of the secondary user achieved under the average transmit power constraint is higher than that achieved under the peak transmit power constraint. It is shown that the design of green cognitive radio should take the tradeoff between its complexity and its achievable maximum energy efficiency into consideration.