Distributed Power Allocation for Cognitive Radio Networks With Time Varying Channel and Delay: H∞ State Feedback Control Approach

被引:6
作者
Zhang, Shuying [1 ]
Zhao, Xiaohui [1 ]
机构
[1] Jilin Univ, Coll Commun Engn, Changchun 1312, Jilin, Peoples R China
基金
中国国家自然科学基金;
关键词
Cognitive radio; power allocation; state-space description; H(infinity )control; RESOURCE-ALLOCATION; WIRELESS NETWORKS; SYSTEMS;
D O I
10.1109/ACCESS.2018.2873804
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
On the basis of H-infinity control approach instead of using the conventional optimization method, we present a distributed power allocation algorithm for a cognitive radio network (CRN), where underlying secondary users (SUs) share same licensed spectrum with primary users (PUs) and the channel gain is time-varying between two time slots. Based on the target signal-to-interference-plus-noise ratio (target-SINR) tracking power control (TPC) algorithm in the conventional network and the dynamic description of the channel gain fluctuation in the CRN as a first-order Markov model, we formulate the power allocation in the CRN into a state-space system model with exogenous input. In this time, the core for us becomes to design a H-infinity state feedback controller obtained by solving a linear matrix inequality (LMI) for this system to realize power allocation for SUs. The SINR requirement of SUs and the interference temperature (IT) constraint of all PUs can be guaranteed. According to this controller design principle, we also give a H-infinity delay-independent state feedback controller to treat time-delay for the protection of the communication performance. Simulation results demonstrate the validity, effectiveness, and advantages of this approach compared with the algorithms obtained by the optimization theory for the power allocation in CRNs.
引用
收藏
页码:56893 / 56910
页数:18
相关论文
共 31 条
[1]  
[Anonymous], 2012, Calculus of Variations and Optimal Control Theory: A Concise Introduction
[2]  
BACCIOTTI A., 2005, Liapunov Functions and Stability in Control Theory, V2nd
[3]  
Boyd S., 1994, SIAM STUDIES APPL MA
[4]   Transmission Power Control for Opportunistic QoS Provision in Wireless Networks [J].
Chaves, Fabiano de Sousa ;
Abbas-Turki, Mohamed ;
Abou-Kandil, Hisham ;
Travassos Romano, Joao Marcos .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2013, 21 (02) :315-331
[5]   LQG Control for MIMO Systems Over Multiple Erasure Channels With Perfect Acknowledgment [J].
Garone, Emanuele ;
Sinopoli, Bruno ;
Goldsmith, Andrea ;
Casavola, Alessandro .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (02) :450-456
[6]   Distributed Resource Management for Cognitive Ad Hoc Networks With Cooperative Relays [J].
Guan, Zhangyu ;
Melodia, Tommaso ;
Yuan, Dongfeng ;
Pados, Dimitris A. .
IEEE-ACM TRANSACTIONS ON NETWORKING, 2016, 24 (03) :1675-1689
[7]   Control theory aspects of power control in UMTS [J].
Gunnarsson, F ;
Gustafsson, F .
CONTROL ENGINEERING PRACTICE, 2003, 11 (10) :1113-1125
[8]  
Hassan N. U., 2013, IEEE COMMUN LETT, V17, P1124
[9]   Cognitive radio: Brain-empowered wireless communications [J].
Haykin, S .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2005, 23 (02) :201-220
[10]   Cognitive Radio Networks: The Spectrum Supply Chain Paradigm [J].
Haykin, Simon ;
Setoodeh, Peyman .
IEEE Transactions on Cognitive Communications and Networking, 2015, 1 (01) :3-28