Comparison of Plane Wave and Spherical Vector Wave Channel Modeling for Characterizing Non-Specular Rough-Surface Wave Scattering
Journal article, 2018

This letter demonstrates advantages of modeling the nonspecular wave scattering from surfaces of a multiple-input multiple-output (MIMO) channel in terms of the spherical vector wave (SVW) mode expansion. We propose the SVW mode coupling matrix M as a more efficient alternative to the commonly used set of distinct plane waves. M incorporates the scattered field components through the limited number of modes due to the cutoff property. A planar surface with random roughness is used to simulate the nonspecular scattering contribution to the radio channel, which is computed using physical optics. The matrix M and the plane wave channel model parameters are estimated from simulated radio channels. The estimates are used to compare the contribution of the nonspecular scattering to the radio channel reproduced from these two approaches. The comparison is performed for a small array antenna arrangement. Compared are the error of themagnitudes of MIMO channel transfer matrix, the narrowband channel eigenvalues, the correlation matrix distance, and the mutual information. It is found that M from the SVW channel modeling performs better in reproducing the radio channel of nonspecular scattering from the studied rough surface.

Distinct plane waves

spherical vector wave (SVW) mode coupling

radio propagation channel

nonspecular wave scattering

Author

Yang Miao

Southern University of Science and Technology

Jun-ichi Takada

Tokyo Institute of Technology

Kentaro Saito

Tokyo Institute of Technology

Katsuyuki Haneda

Aalto University

Andres Alayon Glazunov

University of Twente

Chalmers, Electrical Engineering, Communication and Antenna Systems, Antennas

Yi Gong

Southern University of Science and Technology

IEEE Antennas and Wireless Propagation Letters

1536-1225 (ISSN)

Vol. 17 10 1847-1851

Subject Categories

Telecommunications

Probability Theory and Statistics

Signal Processing

DOI

10.1109/LAWP.2018.2868108

More information

Latest update

3/18/2019