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An improved hybrid implicit-explicit finite-difference time-domain (HIE-FDTD) method is proposed for simulating graphene-based patch couplers at terahertz (THz) for different physical and geometrical parameters, where the Drude model of monolayer graphene and the associated auxiliary differential equation (ADE) technique are implemented. In order to accurately model the curved graphene boundaries, the conformal FDTD method is further hybridized with the HIE-FDTD method, which results in a conformal HIE-FDTD method. Numerical results are presented for S-parameters and field distributions of the coupler, which can be adjusted effectively by changing the chemical potential and layer number of graphene patch or substrate permittivity.

The convolutional perfectly matched layer (CPML) is modified and implemented for one-step leapfrog hybrid implicit-explicit finite-difference time-domain (HIE-FDTD) method. Its stability is verified in a semi-analytical way and its effectiveness is demonstrated numerically. It is shown that even when time step size is large, the absorbing performance of CPML is still very good.Index Term -Convolutional perfectly matched layer (CPML), hybrid implicit-explicit finite-difference time-domain (HIE-FDTD), one-step leapfrog.

Full-wave time-domain electromagnetic methods are usually effective in rigorously modeling and evaluating ultrawideband (UWB) wireless channels. However, their computational expenditures are expensive, when they are used to deal with electrically large-size problems consisting of fine structures. In order to reduce computational time, the unconditionally stable leapfrog alternating-direction implicit finite-difference time-domain (leapfrog ADI-FDTD) method has been proposed recently. In this paper, the leapfrog ADI-FDTD algorithm is developed for simulating lossy objects, such as office walls, floors, and ceilings, for UWB communication channel characterization. It leads to effective UWB channel characterization with power-decay time constant, path loss exponent, and probability distribution of power gain. In comparison with the conventional FDTD, the proposed method can achieve 60% saving in computational time while retaining good accuracy.