DeepMIMOv4: Ray-Tracing Channel Data for 5G and 6G Research

DeepMIMOv4 is a toolchain and database providing ray-tracing datasets for wireless communication research, created by the DeepMIMO organization. Updated in March 2026, it facilitates reproducible machine learning research for 5G and 6G systems using site-specific radio propagation data.

Use Cases

• Training beamforming models using ray-tracing channel parameters like angle of arrival and departure
• Developing wireless sensing applications using site-specific path loss and delay spread data
• Evaluating MIMO channel estimation algorithms using reproducible ray-tracing realizations

Strengths

• Apache-2.0 open-source license
• Supports reproducible research for 5G and 6G
• Provides site-specific ray-tracing parameters

Limitations

• Synthetic data may not capture all nuances of real-world physical environments
• Requires specific software toolchain for full data utilization

Provenance

Source

DeepMIMO

Collection Method

synthetic

Freshness

Last updated March 2026

Geography

Global