Multi-cell Outdoors Channel State Information Dataset (MOCSID)

MOCSID is a multi-cell outdoor channel state information dataset of synthetic channel state information (CSI) samples mimicking an outdoor campus scenario, including multiple base stations with partially overlapping coverage areas and pedestrian user mobility. The scenario is characterized by a high density of base stations (10 base stations within a 625 m x 535 m area) and includes a mixture of non-line-of-sight and line-of-sight propagation. MOCSID includes user locations, timestamps, velocity and multipath component information (delays and path coefficients), following realistic pedestrian user mobility patterns generated using the probabilistic roadmap algorithm, and captures key signal propagation characteristics including path loss, shadowing, and multipath effects. Since MOCSID is intended as a reference for the development and validation of channel charting algorithms, we put particular emphasis on the spatial consistency of the synthetic data. With this dataset, we aim to foster progress in channel charting research by facilitating entry into the field and encouraging reproducibility, collaboration, and benchmarking within the community. MOCSID was generated using the NVIDIA Sionna ray tracing tool; the codebase used to generate the dataset as well as the scene description data and user movement patterns are also publicly available, allowing for easy replication, reproduction, or extension.