Towards Continuous Latency Monitoring through Open RAN Interfaces

We propose DBench, a framework for automated data collection and analysis to infer the processing latency of individual RAN components. DBench interposes on open RAN interfaces, periodically collecting user data traffic and correlating them to provide a detailed breakdown of user-perceived network latency. Developing DBench involves addressing challenges such as mapping low-level raw I/Q samples to individual data packets and handling of high volume of RAN traffic. We overcome these challenges by (1) exploiting the timing characteristics of the 5G New Radio (NR) frame structure at the fronthaul interface, and (2) implementing a pipeline data collection and parallel data processing flow. We demonstrate DBench's capabilities through several use cases on an academic open RAN testbed and discuss ongoing efforts to expand its functionalities and address current limitations.