Paper Info
Title
Nonconvex utility-based power allocation for cognitive radio MIMO system over fading channels
Abstract
In this paper, we present a power control algorithm in cognitive radio multiple-input–multiple-output (MIMO) system over time-varying fading channels based on the utility-based framework. In particular, a more general objective function framework is proposed under a long- or short-term transmitting and interference power constraints for secondary users, which results the optimization problem is nonconvex. A stochastic optimization algorithm is proposed based on an improved quantum-behaved particle swarm optimization (IQPSO), which can solve the nonconvex optimization problem efficiently. The acceleration coefficients are adjusted with time-varying equations which can help the particles jump out the local optimum. Due to the characteristics of wave function of quantum Delta potential well model, IQPSO can get better optimal solutions in search space for the stochastic optimization problem. To show the efficiency of the proposed algorithm, the utilities of the MIMO CR system got by IQPSO are compared with other approaches in the literature in different case studies, which show that the proposed algorithm can solve the nonconvex problem efficiently and achieve significant throughput.
Year
DOI
Venue
2019
10.1007/s00500-018-03746-x
Soft Computing
Keywords
Field
DocType
Cognitive radio (CR), Nonconvex optimization, Particle swarm optimization (PSO), Power allocation
Particle swarm optimization,Mathematical optimization,Stochastic optimization,Computer science,Fading,Local optimum,MIMO,Throughput,Optimization problem,Cognitive radio
Journal
Volume
Issue
ISSN
23.0
22.0
1433-7479
Citations 
PageRank 
References 
0
0.34
12
Authors
3
Name
Order
Citations
PageRank
Meiqin Tang1233.92
Xinjiang Wei29511.33
Wuquan Li300.34