A Robust Distributed Power Control Algorithm for Minimum Interference to Primary Users in Underlay Cognitive Radio Networks

A robust distributed optimal power control (RDPC) scheme under worst case condition is proposed to make primary users (PUs) receive minimum interference generated from all secondary users (SUs) in underlay cognitive radio networks (CRNs). The strategy considers the transmit power of each SU below the maximum allowable power of the devices and interference plus noise ratio (SINR) of each SU under the minimum threshold. Simulation illustrate thatthe RDPC can lead SUs to reduce the interference to PUs, and simultaneously the better meet quality of service (QoS) requirement of SUs in comparison with the distributed power control algorithm (DPC) and the traditional iterative water filling algorithm (IWFA) in time-varying channel environment.

[1]  Lingling Chen,et al.  Power Control Algorithm for Cognitive Radio Based on Chaos Particle Swarm Optimization , 2014 .

[2]  Chen He,et al.  A Novel Price-Based Power Control Algorithm in Cognitive Radio Networks , 2013, IEEE Communications Letters.

[3]  Guoan Bi,et al.  A Simple Distributed Power Control Algorithm for Cognitive Radio Networks , 2011, IEEE Transactions on Wireless Communications.

[4]  Syed Ali Jafar,et al.  Soft Sensing and Optimal Power Control for Cognitive Radio , 2010, IEEE Transactions on Wireless Communications.

[5]  Sanjay Dhar Roy,et al.  Outage and SEP Performance of Secondary User in Spectrum Sharing with Imperfect Channel Estimation , 2014, 2014 Fourth International Conference on Advances in Computing and Communications.

[6]  Yan Chen,et al.  On cognitive radio networks with opportunistic power control strategies in fading channels , 2008, IEEE Transactions on Wireless Communications.

[7]  Simon Haykin,et al.  On Cognitive Dynamic Systems: Cognitive Neuroscience and Engineering Learning From Each Other , 2014, Proceedings of the IEEE.

[8]  Lingling Chen,et al.  An Improved Power Control AFSA for Minimum Interference to Primary Users in Cognitive Radio Networks , 2016, Wirel. Pers. Commun..

[9]  Saeedeh Parsaeefard,et al.  Robust Worst-Case Interference Control in Underlay Cognitive Radio Networks , 2012, IEEE Transactions on Vehicular Technology.

[10]  Sabit Ekin,et al.  Random Subcarrier Allocation in OFDM-Based Cognitive Radio Networks , 2012, IEEE Transactions on Signal Processing.

[11]  Liang Xiao,et al.  Anti-Jamming Transmission Stackelberg Game With Observation Errors , 2015, IEEE Communications Letters.

[12]  Bin Li,et al.  Adaptive power control algorithm in cognitive radio based on game theory , 2015, IET Commun..

[13]  Geoffrey Ye Li,et al.  Cognitive radio networking and communications: an overview , 2011, IEEE Transactions on Vehicular Technology.

[14]  Ekram Hossain,et al.  On Joint Power and Admission Control in Underlay Cellular Cognitive Radio Networks , 2015, IEEE Transactions on Wireless Communications.