An Adjustable Channel Bonding Strategy in Centralized Cognitive Radio Networks and its Performance Optimization

Abstract

One form of spectrum enhancement technologies for cognitive radio networks is a channel bonding strategy, with which a network user can utilize multiple idle channels as one bonding channel. In this paper, we propose an adjustable channel bonding strategy for centralized cognitive radio networks. The main idea is that the number of channels to be aggregated is set according to the number of packets remaining in the system dynamically. Based on the working principle of the proposed adjustable channel bonding strategy, we present a discrete-time priority queueing model with an adjustable transmission rate for this network system. By constructing a two-dimensional Markov chain, we give the transition probability matrix of the Markov chain and obtain the steady-state distribution of the system model. Accordingly, we derive the formulas for the blocking rate, the normalized throughput, the average latency of the Secondary Users (SUs) and the closed channel ratio. Moreover, we provide numerical experiments to investigate the influence of the buffer capacity of the SUs on different performance measures. Finally, with regard to the joining of an SU packet as a trial, we give the Nash equilibrium strategy and socially optimal strategy for the SUs, and propose a reasonable admission fee in order to oblige the SU packets to adopt the socially optimal strategy.

Key Words:

• Adjustable transmission rate
• channel bonding
• cognitive radio networks
• Markov chain
• optimal strategy
• priority queue.

Additional information

Notes on contributors

Yuan Zhao

Yuan Zhao received the B.Eng. degree in mathematics and applied mathematics from Tangshan Normal College, Tangshan, China, the M.Eng. degree in operation science and control theory and Dr.Eng. degree in computer application technology from Yanshan University, Qinhuangdao, China. She is currently a Lecturer at School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China. Her research interests include spectrum allocation in cognitive radio networks, stochastic modeling and system optimization for communication networks, queueing theory and its application.

Shunfu Jin

Shunfu Jin received the B.Eng. degree in computer and application from North East Heavy Machinery College, Qiqihaer, China, the M.Eng. degree in computer science and Dr.Eng. degree in circuit and system from Yanshan University, Qinhuangdao, China. Now Dr. Jin is a Professor at School of Information Science and Engineering, Yanshan University, Qinhuangdao, China. Her research interests include stochastic modeling for telecommunication, performance evaluation for computer system and network, application for queueing system.

Wuyi Yue

Wuyi Yue received the B.Eng. degree in electronic engineering from Tsinghua University, China, and the M.Eng. and Dr.Eng. degrees in applied mathematics and physics from Kyoto University, Japan. She was a researcher and a chief researcher of ASTEM RI, an associate Professor of Wakayama University, an associate Professor and a Professor at the Department of Applied Mathematics, a Professor at Department of Information Science and Systems Engineering, Konan University, Japan. She is currently a Professor at Department of Intelligence and Informatics, Konan University, Japan. She is also the dean of the faculty of Intelligence and Informatics, Konan University, Japan, now. She is a senior member of IEICE of Japan, a fellow of the Operations Research Society of Japan, a member of the IEEE, the System Engineers Society of China and the Operations Research Society of China. Her research interests include queueing theory, stochastic processes and optimal methods as applied to system modeling, performance analysis and evaluation, and optimal resource allocation of wired and wireless/mobile communication networks (including mobile cellular, multi-hop, multi-traffic mobile communication networks), multimedia communication networks, traffic systems, stochastic systems, information systems, systems engineering and operations research.