用速率自适应算法改进车辆仿真网络性能

K. Nwizege, Agbeb N. Stephen, Shedrack Mmeah, Michael MacMammah, I. P. Gibson
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引用次数: 0

摘要

在媒体访问控制层(MAC)下面是物理层(PHY),物理层处理从上面的MAC层接收到的比特实际传输成电磁信号。该层经过优化,以实现无线网络中的电源管理。电源管理是无线和移动网络中的一个关键问题。在本文中,我们提出一种自适应情境感知速率选择(ACARS)算法来处理无线网络中的功耗问题。该算法通过优化物理层来实现,使其随着节点数量的变化而有效传输,并估计物理层的信噪比(SNR)。结果表明,通过采用适当的电源管理技术,ACARS在车载网络对无线网络功耗要求较高的情况下是可靠和高效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Network Performance with Rate Adaptation Algorithms for Vehicular Simulations
Below the Media Access Control (MAC) layer is the Physical (PHY) layer which deals with the actual transmission of the bits received from the MAC layer above into electromagnetic signals. This layer is optimized to implore power management in wireless networks. Power management is a crucial issue in wireless and mobile networks. In this paper, we propose an Adaptive Context-Aware Rate Selection (ACARS) algorithm to handle the issue of power consumption in wireless networks. This algorithm is implemented by optimizing the PHY layer to transmit efficiently as the number of nodes changes and we estimate the Signal-to-Noise Ratio (SNR) to the PHY layer. Results show that by using the appropriate power management technique, ACARS is reliable and efficient for power consumption in wireless networks which is a high demand for vehicular networks.
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