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Outdoor Positioning Algorithms Based on LTE and WiFi Measurements

机译:基于LTE和WiFi测量的室外定位算法

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摘要

This scientific work focuses on outdoor positioning in WLAN and 4G wireless cellular networks based on extensive collection of radio measurements from WiFi and LTE signals, supplied with Global Positioning System location information and time stamp.The objective of work is to explore the performance of different RSS-based outdoor positioning algorithms in terms of distance error and database. The objective includes, through simulating experiments, to verify if accuracy is in compliance with the E911 requirements. The scope of the research is to establish an energy-efficient and low-latency solution for accurate and reliable outdoor positioning based on cellular networks.Two probabilistic models based on coverage-area and path-loss are studied and implemented whereas the more common deterministic model based on classical-fingerprinting is used as benchmark for assessing the performance. The advantage of using probabilistic model over deterministic is that only few parameters per transmitter identification need to be stored and hence there is a significant reduction of the database size. Results show that statistical models suffer accuracy loss to some extent but nevertheless, the decrease in accuracy is not significant with respect to the requirements imposed by FCC.
机译:这项科学研究工作基于WiFi和LTE信号的大量无线电测量结果,并结合全球定位系统的位置信息和时间戳,着重于WLAN和4G无线蜂窝网络中的室外定位,其目的是探索不同RSS的性能。基于距离误差和数据库的户外定位算法。目的包括通过模拟实验来验证准确性是否符合E911要求。本研究的范围是建立一种基于蜂窝网络的高能效,低延迟解决方案,以实现准确,可靠的户外定位。研究并实现了两种基于覆盖面积和路径损耗的概率模型,而较常见的确定性模型基于经典指纹识别的性能作为评估性能的基准。与确定性相比,使用概率模型的优势在于,每个发射机标识仅需要存储很少的参数,因此可以大大减少数据库的大小。结果表明,统计模型在一定程度上遭受准确性损失,但是,相对于FCC提出的要求,准确性的降低并不明显。

著录项

  • 作者

    Soderini Auryn Pink;

  • 作者单位
  • 年度 2016
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  • 原文格式 PDF
  • 正文语种 en
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