A High-resolution Parameter Extraction Algorithm for Multiple Clusters Channels

Multi-path components (MPCs) in wireless channels generally occur in clusters, i.e., groups of MPCs that have similar delay/angle characteristics. However, when those clusters are widely separated and have significantly different power, high-resolution parameter extraction (HRPE) algorithms based on serial interference cancellation, such as CLEAN, can miss some of the weaker clusters because they concentrate the path search in the strongest cluster. This effect can occur particularly in the presence of calibration error and/or diffuse scattering. To solve this problem, we propose a heuristic modification, Regional CLEAN (R-CLEAN) that employs cluster identification in the Fourier domain and limits the number of MPCs per cluster. We first demonstrate the effect, and the effectiveness of our proposed algorithm, on synthetic channels with calibration error or diffuse scattering. We then demonstrate it with a THz Multiple-Input-Multiple-Output (MIMO) measurement at 145 - 146 GHz. The proposed optimization and algorithm can thus be an essential step towards evaluating channels with multiple clusters.