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RSSI-based localization in cellular networks

机译:蜂窝网络中基于RSSI的本地化

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This paper presents a novel RSSI based localization scheme that employs an existing cellular network infrastructure to perform trilateration. Traditional localization schemes employ RSSI-based radial distance estimation and trilateration algorithm. However, in a realistic scenario, the RSSI measurements are distorted due to multipath fading thus introducing error in radial distance estimation. Moreover, the selection of the best three anchor cell towers with the lowest localization error is not been explored. The proposed scheme improves localization accuracy using two, novel correcting and evaluating metrics: the Radial Distance Error Indicator (RDEI) and the Localization Error Indicator (LEI). The proposed RDEI metric is derived from the mean square error (MSE) of radial distance estimation in multipath fading channel. In the proposed method, it is employed as a correcting factor for the radial distance estimation. Next, the LEI estimate the combined localization error based on the towers positions, corresponding radial distance estimation and its error. The final position estimation improves localization accuracy as demonstrated through analytical and experimental results.
机译:本文提出了一种新颖的基于RSSI的定位方案,该方案采用了现有的蜂窝网络基础设施来执行三边测量。传统的定位方案采用基于RSSI的径向距离估计和三边测量算法。但是,在实际情况下,由于多径衰落,RSSI测量值会失真,从而在径向距离估计中引入误差。而且,没有探索具有最小定位误差的最佳三个锚单元塔。所提出的方案使用两个新颖的校正和评估指标来提高定位精度:径向距离误差指示器(RDEI)和定位误差指示器(LEI)。所提出的RDEI度量是从多径衰落信道中径向距离估计的均方误差(MSE)中得出的。在提出的方法中,它被用作径向距离估计的校正因子。接下来,LEI根据塔位置,相应的径向距离估计及其误差来估计组合的定位误差。通过分析和实验结果证明,最终位置估计可以提高定位精度。

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