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Transmission capacity analysis for cellular based cognitive radio VANETs

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Abstract

This paper presents a framework of cellular based cognitive-radio vehicular ad hoc networks (CCR-VANETs) that consists of a cellular network (primary network) and VANET (secondary network). These coexisting networks share the uplink spectrum of the cellular network. Although some scaling law-based results on VANETs have been presented for the description of performance changing patterns, they are unsuitable for CCR-VANET and cannot be directly used for estimating the capacity of the communication pairs in the entire network. In this study, we apply the interference-based transmission capacity analysis for CCR-VANET scenario. The classic car-following model is used to describe the moving pattern of all buses and vehicles, and a two-phase CSMA based on the opportunistic spectrum access (OSA) protocol of the secondary network is adopted. Then the calculation of the transmission opportunity is obtained. After that, the outage probability is analyzed, in which just the first layer of interferers in both primary and secondary networks are considered, as a result of the bound effect of interference power in the wireless network. With the obtained results on outage probability under the worst interfered scenario, we characterize a lower bound on transmission capacity of the secondary network. Finally, the simulation results are conducted to validate our analytical results, and also to give an analysis of the average transmission capacity trade-off between the primary and secondary networks.

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Acknowledgments

This work is supported in part by the National Natural Science Foundation of China under Grant Nos. 61271184 and 61571065.

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Authors and Affiliations

  1. Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Xinxin He, Hang Zhang & Tao Luo

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  1. Xinxin He
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Correspondence to Xinxin He.

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He, X., Zhang, H. & Luo, T. Transmission capacity analysis for cellular based cognitive radio VANETs. Wireless Netw 23, 2215–2226 (2017). https://doi.org/10.1007/s11276-016-1280-5

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