In order to realize the future Sixth-Generation (6G), the research on Integrated Sensing and Communication (ISAC) channel modeling has attracted considerable attention. In classical cluster-based models, it is difficult to effectively build high density point clouds to outline object features. As an alternative, slightly-distributed-scatterer-based signal models are utilized in this paper, and a first-order generalized array manifold is used to approximate the spread features of channel. By combining this with the space-alternating generalized expectation-maximization (SAGE) algorithm, we achieve a framework for the efficient estimation of the dispersive-path components including the spread on the angle and the Doppler frequency domains. Based on measured data in vehicular environments, the effectiveness of the algorithm is verified, and a time-varying statistical channel model is formulated. The results obtained can help to accurately model vehicular channels and provide guidance for other applications of autonomous driving.
Slight-Distributed-Scatterer-Based Time-Varying Channel Modeling for Vehicular Environments
2024-06-24
4192363 byte
Conference paper
Electronic Resource
English
Cluster-based scatterer identification and characterization in vehicular channels
Tema Archive | 2011
|Scatterer based airport surface channel model
IEEE | 2009
|Vehicular Channel Characteristics and Modeling
Springer Verlag | 2018
|