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The higher the better? Think twice!

机译:越高越好?想三思!

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摘要

As research interest in the Internet of Things continue to grow, concerns are raised regarding potential limitations of the current body of knowledge on performance engineering for wireless links. Best practices in this thematic area have insofar largely been focused on human-to-human communications (e.g., wide area cellular wireless networks) and traffic patterns emerging from human actions (e.g., asymmetric bandwidth between the uplink and downlink traffic directions) in urban areas. As a result, studies of the propagation profile that would properly characterize the deployment of wireless technologies (e.g., sensor networks) in rural areas and for specific applications of machine-to-machine (M2M) communications are not sufficiently developed in the literature. To address this shortcoming, we collect and study RSSI measurements as a function of base station antenna height and at a certain distance and transmitting antenna height, under a rural setting. The measurements collected from our testbed instrumentation seem to follow closely the theoretical two-ray model. It is therefore shown here that whenever a second ray has impact on propagation characteristics there is always an optimum and minimum base station antenna height. A method for defining those heights is presented in this paper, which further allows performance optimisation of a wireless sensor network.
机译:随着对事物互联网的研究兴趣继续增长,涉及目前关于无线链路性能工程知识潜在局限性的潜在限制。该主题区域的最佳实践在很大程度上主要集中在人对人类通信(例如,广域蜂窝织无线网络)和城市区域中的人类行为(例如,上行链路和下行链路交通方向之间的不对称带宽)中出现的流量模式。结果,对农村地区的无线技术(例如,传感器网络)和机器上的特定应用进行正确表征的传播简档,并且在文献中不充分开发。为了解决这种缺点,我们将RSSI测量作为基站天线高度和在农村环境下的一定距离和传输天线高度的函数。从我们的测试用仪器收集的测量似乎密切关注理论双射线模型。因此,这里示出了,每当第二射线对传播特性的影响时,总是存在最佳和最小基站天线高度。本文介绍了一种用于定义这些高度的方法,其进一步允许无线传感器网络的性能优化。

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