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Since the terahertz frequency band (0.1–1 THz) has attracted considerable attention for the upcoming sixth-generation (6G) wireless communication systems, accurate models for multipath propagation in this frequency range need to be established. Such models advantageously use the fact that multi-path components (MPCs) occur typically in clusters, i.e., groups of MPCs that have similar delays and angles. In this paper, we first analyze the limitations of a widely used clustering algorithm, Kernel-Power-Density (KPD), in evaluating an extensive THz outdoor measurement campaign at 145–146 GHz, particularly its inability to detect small clusters. We introduce a modified version, which we term multi-level KPD (ML-KPD), iteratively applying KPD to detect whether a cluster determined in the previous round is made up of multiple clusters. We first apply the method to synthetic channels to demonstrate its efficacy and select suitable values for the adaptive hyperparameters. Then, multi-level KPD is applied to our channel measurements in line-of-sight (LOS) and non-line-of-sight (NLOS) environments to determine statistics for the number of clusters and the cluster spreads.
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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, highresolution 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.
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- PAR ID:
- 10342404
- Date Published:
- Journal Name:
- IEEE SPAWC 2022
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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