A Fast Ray-tracing-based Algorithm for Very Low Frequency Radio Propagation

Cao, Yuwei; Liu, Zhongyu; Guo, Lixin

doi:10.1109/csqrwc.2019.8799246

Cited by 1 publication

(1 citation statement)

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“…Computer simulations can be optimized through extensive computer simulations and measurements. The ray tracing method [7][8][9][10], which is widely used in indoor and outdoor wireless channel propagation, is an effective means to conduct research on channel models in the millimeter wave. The ray tracing method can better assess the problem of electromagnetic wave propagation and is widely used in the channel modeling of millimeter waves.…”

Section: Introductionmentioning

confidence: 99%

Research on Propagation Characteristics Based on Channel Measurements and Simulations in a Typical Open Indoor Environment

Hou,

Li,

Zhang

et al. 2023

Electronics

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At present, it is difficult to obtain the indoor propagation loss quickly and accurately by directly using measurements in the millimeter wave band. To solve this problem, in this paper, a ray tracing method suitable for indoor scenes based on geometric optics theory, the uniform theory of diffraction and image theory is presented; the space-alternation generalized expectation-maximization (SAGE) algorithm is used to analyze the measured data and the multipath information of the wireless channel is analyzed; three deep learning models are used to predict the path loss at different receiving distances based on 1600 sets of path loss data. The results show that the comparison between the ray tracing and experimental results shows a good agreement. Moreover, the root-mean-square error (RMSE) and mean absolute error (MAE) of the long short-term memory (LSTM) network are the smallest, and the LSTM has a better fitting effect on the propagation loss sequences predicted at more distant locations when compared with the recurrent neural network (RNN) and gate recurrent unit (GRU) methods, which can better reflect the propagation trend. This provides theoretical support for the layout of base stations and network optimization in typical open indoor environments.

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Section: Introductionmentioning

confidence: 99%