Adjustable admission control with threshold in centralized CR networks: Analysis and optimization

Yuan Zhao; Shunfu Jin; Wuyi Yue

doi:10.3934/jimo.2015.11.1393

Article Contents

2015, Volume 11, Issue 4: 1393-1408. Doi: 10.3934/jimo.2015.11.1393

This issue Previous Article Optimal double-resource assignment for a distributed multistate network Next Article Existence and stability analysis for nonlinear optimal control problems with $1$-mean equicontinuous controls

Adjustable admission control with threshold in centralized CR networks: Analysis and optimization

1.
School of Information Science and Engineering, Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan University, Qinhuangdao 066004
2.
Department of Intelligence and Informatics, Konan University, Kobe 658-8501

Received: January 31, 2014

Revised: September 30, 2014

Published: September 2015

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Abstract

In order to enhance the Quality of Service (QoS) for the secondary users (SUs) in Cognitive Radio (CR) networks reasonably, in this paper, we propose an adjustable admission control scheme considering an access threshold under a centralized architecture. We assume that a buffer is set for all the SUs. On the arrival instant of an SU packet, if the number of SU packets already in the buffer is equal to or greater than the access threshold that is set in advance, this SU packet will be admitted to join the system with an adjustable access probability, which is inversely proportional to the total number of packets in the system. Based on the adjustable admission control scheme proposed in this paper, considering the priority of the primary users (PUs) in CR networks, we build a preemptive priority queueing model. Aiming to comply with the digital nature of modern networks, we establish a two-dimensional discrete-time Markov chain (DTMC) and construct the transition probability matrix of the Markov chain. Accordingly, we provide the formulas for several performance measures, such as the blocking rate, the throughput and the average latency of the SU packets. With numerical results, we show the influence of the access threshold on different performance measures for the SU packets. Finally, taking into account the trade-off between different performance measures, we build a net benefit function to find the optimal access threshold with an optimization algorithm.

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Mathematics Subject Classification: Primary: 68M10, 68M20; Secondary: 60J10.

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