Receivers with an antenna array based on the assumption of Gaussian noise have experienced poor performance in extremely lowfrequency/very-low-frequency (ELF/VLF) communication systems, in which the noise is highly impulsive. In this paper, a blind receiver with multiple antennas for channels with impulsive noise is developed to estimate signal and channel parameters jointly by using the Markov chain Monte Carlo (MCMC) algorithm. The impulsive noise is modeled as the subGaussian distribution, which is widely applied. Simulation results show that the blind receiver can rapidly converge, and excellent performance can be achieved.Index Terms-Impulsive noise, Markov chain Monte Carlo (MCMC) algorithm, mixture model, symmetric alpha-stable (SαS) distribution.
Numerical simulations of flooding events through rivers and channels require coupling between one-dimensional (1D) and two-dimensional (2D) hydrodynamic models. The rivers and channels are relatively narrow, and the widths could be smaller than the grid size used in the background 2D model. The shapes of the rivers and channels are often complex and do not necessarily coincide with the grid points. The coupling between the 1D and 2D models are challenging. In this paper, a novel immersed-boundary (IB) type coupling is implemented. Using this method, no predetermined linking point is required, nor are the discharge boundary conditions needed to be specified on the linking points. The linkage will be dynamically determined by comparing the water levels in the 1D channel and the surrounding dry cell elevations on the 2D background. The linking-point flow conditions, thus, can be dynamically calculated by the IB type implementation. A typical problem of the IB treatment, which is the forming of the nonsmooth zigzag shaped boundary, has not been observed with this method. This coupling method enables more realistic and accurate simulations of water exchange between channels and dry lands during a flooding event.
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