Conformal FDTD method for simulating the interaction of an EMP with multiple PEC/dielectric wedge structures

Xie, Hao; Yuan, Xiang; Wang, Yin; Li, Er‐Ping; Zhao, Z.; Zhou, Haijing

doi:10.1109/apemc.2016.7522932

Cited by 1 publication

(1 citation statement)

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“…In order to reduce the staircase error, several hybrid subgridding techniques have been proposed in reference 11–13, but it is difficult to eliminate the reflection between cell boundaries by using these methods. Therefore, the conformal finite‐difference time‐domain (CFDTD) method is proposed, 14–17 which improves the computational accuracy of the curved objects without using fine meshes. However, these techniques are mainly related to non‐dispersive FDTD methods.…”

Section: Introductionmentioning

confidence: 99%

Modeling of indoor network channels with dispersive media based on a modified CFDTD method

Shi

Wang

Zhang

et al. 2022

Int J Numerical Modelling

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In order to investigate the electromagnetic (EM) propagation characteristics and further get the channel models for indoor environments, a modified conformal finite-difference time-domain (CFDTD) method is introduced in this paper. Specifically, the dispersion characteristics of media are modeled by using the auxiliary differential equation (ADE) technique of the Debye model, and the EM field iterative equation is obtained by weighted-length of various media in the conformal cells for the curved structure. The proposed method is used to simulate the channels of 2.4 GHz wireless fidelity (Wi-Fi) network and 5G microcellular network, respectively, for the single-and complex multiroom scenarios. The impulse response, power delay profile and path loss exponent are extracted from the simulation data to analyze the effective ultrawideband (UWB) channel characteristics. Compared with the traditional FDTD, the proposed method has the advantage of obtaining a stable and good accuracy solution and reducing the time step without the need to solve highorder differential equations.

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Section: Introductionmentioning

confidence: 99%