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Optimization of handover measurement procedure for TD-LTE networks in mountainous scenario

机译:山区场景下TD-LTE网络切换测量过程的优化

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Handover (HO) is a key procedure in long term evolution (LTE) systems. This paper makes a detailed introduction on two aspects in HO measurement procedure—Layer3 filtering theory and the radio link failure (RLF) procedure. As the channel environment in mountainous scenario has a great effect on received signal, we have made researches and optimizations on user equipment (UE) measurement signal accordingly. HO procedure based on Layer3 (L3) filtering and optimized RLF procedure are designed and implemented in a dynamic system level simulation platform which models the mountainous scenario. The UE measured Reference Signal Received Power (RSRP) of source and target eNodeB with different L3 filtering factor have been measured to make a comparison and select the best one. Ping-pong HO rate and RLF rate are used to evaluate the influence of L3 filtering to HO performance. Simulation results show that the best L3 filtering factor is 1/6 and the optimized RLF procedure is effective in mountainous scenario. The paper presents a new fast interpolation method based on edge extraction. Our method extracts image edge by improved canny operator which has two specified thresholds first. Then for different areas, it chooses different methods. It can keep edge details while doing quick interpolation. The experimental results show that the effect of this method can hold the edge details very well, and it is obviously superior to the traditional ways. The method provides a better initial image for the super resolution reconstruction.
机译:切换(HO)是长期演进(LTE)系统中的关键过程。本文对HO测量过程的两个方面进行了详细介绍,即第3层滤波理论和无线链路故障(RLF)过程。由于山区环境中的信道环境对接收信号影响很大,因此我们对用户设备(UE)测量信号进行了研究和优化。在对山区场景进行建模的动态系统级仿真平台中,设计和实现了基于第3层(L3)过滤的HO程序和优化的RLF程序。 UE测量了具有不同L3滤波因子的源和目标eNodeB的参考信号接收功率(RSRP),以进行比较并选择最佳的参考信号接收功率。乒乓切换速率和RLF速率用于评估L3过滤对切换性能的影响。仿真结果表明,最佳的L3滤波系数为1/6,优化的RLF程序在山区环境中是有效的。提出了一种新的基于边缘提取的快速插值方法。我们的方法通过改进的Canny算子提取图像边缘,该算子首先有两个指定的阈值。然后针对不同的区域,选择不同的方法。快速插值时可以保留边缘细节。实验结果表明,该方法能够很好地保持边缘细节,明显优于传统方法。该方法为超分辨率重建提供了更好的初始图像。

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