Power Allocation with Max---Min and Min---Max Fairness for Cognitive Radio Networks with Imperfect CSI

  • Authors:
  • Tang Lun;Yan Jing-Lin;Li Qing;Chen Qian-Bin;Wang Huan

  • Affiliations:
  • School of Communication and Information Engineering, ChongQing University of Posts and Telecommunications, ChongQing, China 400065;School of Communication and Information Engineering, ChongQing University of Posts and Telecommunications, ChongQing, China 400065;School of Communication and Information Engineering, ChongQing University of Posts and Telecommunications, ChongQing, China 400065;School of Communication and Information Engineering, ChongQing University of Posts and Telecommunications, ChongQing, China 400065;School of Communication and Information Engineering, ChongQing University of Posts and Telecommunications, ChongQing, China 400065

  • Venue:
  • Wireless Personal Communications: An International Journal
  • Year:
  • 2012

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Abstract

This paper consider the power allocation strategies in the cognitive radio (CR) system in the presence of channel estimation errors. As the user has different channel condition in CR systems, different amount of power resource is required to meets the QoS request. In order to guarantee the fairness of each CR user, ensure the interference from the primary user and other CR users meet the QoS requirement of the CR user and limit the interference that is caused by CR users on primary user within the range into the level that primary user can tolerate, we proposed some new power allocation schemes. The targets are to minimize the maximum power allocated to CR users, to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all CR users and to minimize the maximum outage probability over all CR users. The first power allocation scheme can be formulated using Geometric Programming (GP). Since GP problem is equivalent to the convex optimization problem, we can obtain the optimal solutions for the first scheme. The latter two power allocation schemes are not GP problems. We propose iterative algorithms to solve them. Simulation results show that proposed schemes can efficiently guarantee the fairness of CR users under the QoS constraint of the primary user and CR users.