AAF: Analog superposition assisted forwarding node selection and density estimation in vehicular networks

P. Sahu, A. Hafid
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引用次数: 1

Abstract

In this paper, we propose an efficient forwarding node selection and density estimation mechanisms for vehicular networks (VANETs). Density estimation is performed without using beacons. Basically, the transmission range is divided into segments. Then, we apply a superposition based analog signal transmission and exploit multi-user capability of OFDM to collect density in each lane and in each segment. With such fine-grained information, a farthest node can be successfully located and selected as the forwarder. The one hop delay is substantially reduced by reducing the contention time and relying mostly on signals instead of control packets to assist the forwarder node selection process. In the simulations, it is observed that the proposed protocol accurately estimates the node density. Also, it outperforms existing multi-hop broadcast protocols in terms of end-to-end delay.
模拟叠加辅助车辆网络转发节点选择与密度估计
本文提出了一种高效的车载网络转发节点选择和密度估计机制。在不使用信标的情况下进行密度估计。基本上,传输范围被分成几个段。然后,我们采用基于叠加的模拟信号传输,利用OFDM的多用户能力来采集每个信道和每个线段的密度。有了这些细粒度的信息,就可以成功地定位并选择最远的节点作为转发器。通过减少争用时间和主要依靠信号而不是控制数据包来辅助转发器节点选择过程,大大减少了一跳延迟。仿真结果表明,该协议能够准确地估计节点密度。此外,它在端到端延迟方面优于现有的多跳广播协议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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