An imperfect sensing-based channel reservation strategy in CRNs and its performance evaluation

Jianping Liu; Shunfu Jin

doi:10.3934/jimo.2018197

Article Contents

2020, Volume 16, Issue 3: 1149-1169. Doi: 10.3934/jimo.2018197

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An imperfect sensing-based channel reservation strategy in CRNs and its performance evaluation

Jianping Liu^1,2,3, and
Shunfu Jin^1,3, ,

1.
School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
2.
Hebei Normal University of Science and Technology, Qinhuangdao, China
3.
Science and Technology on Communication Networks Laboratory, Shijiazhuang, China

^*Corresponding author: Shunfu Jin
^*Corresponding author: Shunfu Jin

Received: September 30, 2017

Revised: December 31, 2017

Early access: December 2018

Published: March 2020

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Abstract

Channel reservation strategy in CRNs is an effective technology for conserving communication resources. In this paper, using the imperfect sensing of secondary user (SU) packets, and considering the patience degree of SU packets, we propose a channel reservation strategy in a CRN. Aligned with the proposed channel reservation strategy, we establish a continuous-time Markov chain model to capture the stochastic behavior of the two types of user packets. Then, in order to obtain the steady-state probability distribution for the system model, we present a new algorithm for solving the quasi-birth-and-death (QBD) process. At last, based on the energy detection method, we evaluate the system performance in terms of the throughput of SU packets, the average latency of SU packets, the switching rate of SU packets and the channel utilization in relation to the energy detection threshold and the number of reserved channels.

Keywords:

Mathematics Subject Classification: Primary: 60K25, 90B22; Secondary: 68M20, 68M10.

Citation:

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Figure 1. The transmission process of the user packets in the system

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Figure 2. Throughput $ \rho_{su} $ of SU packets vs. the energy detection threshold $ \tau $

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Figure 3. Average latency $ \beta_{su} $ of SU packets vs. the energy detection threshold $ \tau $

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Figure 4. Switching rate $ \omega_{su} $ of SU packets vs. the energy detection threshold $ \tau $

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Figure 5. Channel utilization $ \sigma $ vs. the energy detection threshold $ \tau $

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Figure 6. Throughput $ \rho_{su} $ of SU packets vs. the number $ N $ of reserved channels

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Figure 7. Average latency $ \beta_{su} $ of SU packets vs. the number $ N $ of reserved channels

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Figure 8. Switching rate $ \omega_{su} $ of SU packets vs. the number $ N $ of reserved channels

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Figure 9. Channel utilization $ \sigma $ vs. the number $ N $ of reserved channels

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