Enabling Programmable Inference and ISAC at the 6GR Edge with dApps

TL;DR

This paper explores how programmable, open RAN architectures can enable real-time AI inference and ISAC at the 6G edge, leveraging dApps and controllers for flexible, dynamic system operation.

Contribution

It introduces the concept of dApps and a hierarchy of controllers to facilitate real-time AI inference and sensing in open RAN, addressing current architectural limitations.

Findings

Exposing I/Q samples and telemetry enables sensing applications.

dApps and controllers support dynamic inference and ISAC.

Experimental results validate the approach on an open-source RAN testbed.

Abstract

The convergence of communication, sensing, and Artificial Intelligence (AI) in the Radio Access Network (RAN) offers compelling economic advantages through shared spectrum and infrastructure. How can inference and sensing be integrated in the RAN infrastructure at a system level? Current abstractions in O-RAN and 3GPP lack the interfaces and capabilities to support (i) a dynamic life cycle for inference and Integrated Sensing and Communication (ISAC) algorithms, whose requirements and sensing targets may change over time and across sites; (ii) pipelines for AI-driven ISAC, which need complex data flows, training, and testing; (iii) dynamic device and stack configuration to balance trade-offs between connectivity, sensing, and inference services. This paper analyzes the role of a programmable, software-driven, open RAN in enabling the intelligent edge for 5G and 6G systems. We identify real-time user-plane data exposure, open interfaces for plug-and-play inference and ISAC models, closed-loop control, and AI pipelines as elements that evolutions of the O-RAN architecture can uniquely provide. Specifically, we describe how dApps - a real-time, user-plane extension of O-RAN - and a hierarchy of controllers enable real-time AI inference and ISAC. Experimental results on an open-source RAN testbed demonstrate the value of exposing I/Q samples and real-time RAN telemetry to dApps for sensing applications.