The reviewed record of science sign in
Pith

arxiv: 2308.13789 · v1 · pith:3N7Z3NHW · submitted 2023-08-26 · eess.SP

Sensiverse: A dataset for ISAC study

Jiajin Luo , Baojian Zhou , Yang Yu , Ping Zhang , Xiaohui Peng , Jianglei Ma , Peiying Zhu , Jianmin Lu
show 1 more author
Wen Tong
This is my paper

Reviewed by Pithpith:3N7Z3NHWopen to challenge →

classification eess.SP
keywords datasetisacsensiversechannelevaluationmodelsresearchacquisition
0
0 comments X
read the original abstract

In order to address the lack of applicable channel models for ISAC research and evaluation, we release Sensiverse, a dataset that can be used for ISAC research. In this paper, we present the method of generating Sensiverse, including the acquisition and formatting of the 3D scene models, the generation of the channel data and associations with Tx/Rx deployment. The file structure and usage of the dataset are also described, and finally the use of the dataset is illustrated with examples through the evaluation of use cases such as 3D environment reconstruction and moving targets.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. AirFM-DDA: Air-Interface Foundation Model in the Delay-Doppler-Angle Domain for AI-Native 6G

    cs.LG 2026-04 unverdicted novelty 6.0

    AirFM-DDA reparameterizes wireless channel data into the delay-Doppler-angle domain and uses efficient window attention to achieve better zero-shot performance on channel prediction and estimation with lower compute cost.