Equilibrium analysis of an opportunistic spectrum access mechanism with imperfect sensing results

Shunfu Jin; Wuyi Yue; Shiying Ge

doi:10.3934/jimo.2016071

Article Contents

2017, Volume 13, Issue 3: 1255-1271. Doi: 10.3934/jimo.2016071

This issue Previous Article Stability of a queue with discriminatory random order service discipline and heterogeneous servers Next Article Optimal Sharpe ratio in continuous-time markets with and without a risk-free asset

Equilibrium analysis of an opportunistic spectrum access mechanism with imperfect sensing results

1.
School of Information Science and Engineering, Key Laboratory for Computer Virtual Technology, and System Integration of Hebei Province, Yanshan University, Qinhuangdao 066004, China
2.
Department of Intelligence and Informatics, Konan University, Kobe 658-8501, Japan
3.
School of Information Science and Engineering, Key Laboratory for Computer Virtual Technology, and System Integration of Hebei Province, Yanshan University, Qinhuangdao 066004, China

Received: October 2015

Published: September 2017

Abstract / Introduction Full Text(HTML) Figure(7) / Table(2) Related Papers Cited by

Abstract

In order to reduce the average delay of secondary user (SU) packets and adapt to various levels of tolerance for transmission interruption, we propose a novel opportunistic channel access mechanism with admission threshold and probabilistic feedback in cognitive radio networks (CRNs). Considering the preemptive priority of primary user (PU) packets, as well as the sensing errors of missed detection and false alarm caused by SUs, we establish a type of priority queueing model in which two classes of customers may interfere with each other. Based on this queueing model, we evaluate numerically the proposed mechanism and then present the system performance optimization. By employing a matrix-geometric solution, we derive the expressions for some important performance measures. Then, by building a reward function, we investigate the strategies for both the Nash equilibrium and the social optimization. Finally, we provide a pricing policy for SU packets to coordinate these two strategies. With numerical experiments, we verify the effectiveness of the proposed opportunistic channel access mechanism and the rationality of the proposed pricing policy.

Keywords:

Mathematics Subject Classification: Primary: 68M10, 68M20; Secondary: 60J28.

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Figure 1. Transmission process of a PU packet

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Figure 2. Transmission process of an SU packet

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Figure 3. Throughput $\phi$ of SU packets

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Figure 4. Block rate $\beta$ of SU packets

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Figure 5. Average delay $W(\lambda_{su})$ of SU packets

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Figure 6. Change trend for the net benefit of an SU packet

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Figure 7. Change trend for the social welfare

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Table 1. Parameter settings in numerical experiments

Parameters	Values
slot	1 ms
transmission rate in physical layer	11 Mbps
arrival rate of SU packets	0.3
mean size of an SU packet	1760 Byte
arrival rate of PU packets	0.05
mean size of a PU packet	2010 Byte
feedback probability	0.0-1.0
energy threshold	1.0-7.0
simulation scale	3 million slots
sensing time	0.1 ms
sensing frequency	10 times/ms

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Table 2. Numerical results for the admission price $F$

Admission threshold $H$	Admission probability $r$	Feedback probability $q$	Admission price $F$
4	0.4	0.4	1.0873
3	0.4	0.4	1.0687
2	0.4	0.4	1.0272
2	0.4	0.0	1.0341
2	0.4	0.7	1.0163
2	0.8	0.7	1.0640
2	0.1	0.7	0.9938

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