Statistical Trilateration With Skew-t Distributed Errors in LTE Networks
Statistical Trilateration With Skew-t Distributed Errors in LTE Networks
复制标题
LTE 网络中具有 Skew-t 分布误差的统计三边测量
DOI：
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发表时间：
2016
影响因子：
10.4
通讯作者：
G. Seco
中科院分区：
文献类型：
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作者：
Philipp Müller;J. A. D. Peral;R. Piché;G. Seco
长期演进（LTE）蜂窝网络中基于到达时间的三边定位方法，由于城市和室内环境中的多路径和非视线条件，定位精度可能会严重降低。多径缓解技术通常涉及高计算负担，并且需要宽带信号有效，这限制了它们在使用窄带信号的某些低成本和低功耗移动应用中的采用。作为这些传统技术的替代方案，本文分析了一种考虑LTE测距误差分布中多径引入的偏性的期望最大化（EM）定位算法。在1.4 mhz带宽的真实LTE仿真信号中对EM算法进行了广泛的研究。在理想的模拟条件下，并利用实验室试验台的实际室外测量结果，将电磁方法与标准非线性最小二乘（NLS）算法进行了比较。当训练阶段和测试阶段的测距误差分布相似时，EM方法优于NLS方法。
Localization accuracy of trilateration methods in long term evolution (LTE) cellular networks, which are based on time-of-arrival, may be highly degraded due to multipath and non-line of sight conditions in urban and indoor environments. Multipath mitigation techniques usually involve a high computational burden and require wideband signals to be effective, which limit their adoption in certain low-cost and low-power mobile applications using narrow-band signals. As an alternative to these conventional techniques, this paper analyzes an expectation maximization (EM) localization algorithm that considers the skewness introduced by multipath in the LTE ranging error distribution. The EM algorithm is extensively studied with realistic emulated LTE signals of 1.4-MHz bandwidth. The EM method is compared with a standard nonlinear least squares (NLS) algorithm under ideal simulated conditions and using realistic outdoor measurements from a laboratory testbed. The EM method outperforms the NLS method when the ranging errors in the training and test stages have similar distributions.