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A Hidden Markov Model based scheme for efficient and fast dissemination of safety messages in VANETs

机译:一种基于隐马尔可夫模型的方案,用于在VANET中高效,快速地传播安全消息

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Nowadays, Vehicle to Vehicle (V2V) communication is attracting an increasing attention from car manufacturers due to its expected impact in improving driving safety and comfort. IEEE 802.11P is the primary channel access scheme used by vehicles; however it does not provide sufficient spectrum to ensure reliable exchange of safety information. To overcome this issue, many efforts have been devoted to enhance the frequency spectrum utilization efficiency. To this end, the Cognitive Radio (CR) principle has been applied to assist the vehicles to gain extra bandwidth through an opportunistic use of the unused spectrums in their surrounding. In this paper, we focus on safety messages for which we propose an original scheme that makes their exchange among the nearby vehicles more reliable with a significant reduce in their dissemination delay. This improvement is due to the use of a Hidden Markov Model that enables the prediction of the available channels for the subsequent time slots, leading to faster channel allocation for the vehicles. The obtained simulation results confirm the efficiency of our scheme.
机译:如今,由于车辆对车辆(V2V)通信在改善驾驶安全性和舒适性方面具有预期效果,因此越来越受到汽车制造商的关注。 IEEE 802.11P是车辆使用的主要信道访问方案。但是,它没有提供足够的频谱来确保安全信息的可靠交换。为了克服这个问题,已经进行了许多努力来提高频谱利用效率。为此,认知无线电(CR)原理已被应用来帮助车辆通过机会性利用周围未使用的频谱来获得额外的带宽。在本文中,我们集中于安全消息,为此我们提出了一个原始方案,该方案使它们在附近车辆之间的交换更加可靠,并大大减少了其传播延迟。这种改进是由于使用了隐马尔可夫模型,该模型能够预测后续时隙的可用信道,从而为车辆提供更快的信道分配。获得的仿真结果证实了我们方案的有效性。

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