dApps: Enabling Real-Time AI-Based Open RAN Control

2025-01-27

AI Summary

To address severe spectrum contention and data-access bottlenecks in 5G open RAN—caused by privacy constraints and latency limitations of the RAN Intelligent Controller (RIC)—this paper proposes a decentralized AI application (dApp) architecture that embeds real-time intelligent control directly into RAN nodes, enabling microsecond-scale closed-loop resource management. We introduce the first dApp reference architecture and full lifecycle model; design a lightweight E3 interface and protocol; and support cross-layer coordination among dApps, xApps, and rApps with hierarchical resource conflict management. Leveraging OpenAirInterface, we implement an open-source dApp framework integrating both E3 and O-RAN E2 interfaces, supporting structured messaging and extensible communication. Experimental validation on a 5G gNB demonstrates two use cases—spectrum sharing and device localization—achieving sub-450 μs average control latency and significantly improved spectrum utilization efficiency.

Technology Category

• Planning, Routing, and Scheduling: Applications
• Search and Optimization: Distributed Search
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Security and Privacy: Security and privacy of machine learning and AI applications

Abstract

Open Radio Access Networks (RANs) leverage disaggregated and programmable RAN functions and open interfaces to enable closed-loop, data-driven radio resource management. This is performed through custom intelligent applications on the RAN Intelligent Controllers (RICs), optimizing RAN policy scheduling, network slicing, user session management, and medium access control, among others. In this context, we have proposed dApps as a key extension of the O-RAN architecture into the real-time and user-plane domains. Deployed directly on RAN nodes, dApps access data otherwise unavailable to RICs due to privacy or timing constraints, enabling the execution of control actions within shorter time intervals. In this paper, we propose for the first time a reference architecture for dApps, defining their life cycle from deployment by the Service Management and Orchestration (SMO) to real-time control loop interactions with the RAN nodes where they are hosted. We introduce a new dApp interface, E3, along with an Application Protocol (AP) that supports structured message exchanges and extensible communication for various service models. By bridging E3 with the existing O-RAN E2 interface, we enable dApps, xApps, and rApps to coexist and coordinate. These applications can then collaborate on complex use cases and employ hierarchical control to resolve shared resource conflicts. Finally, we present and open-source a dApp framework based on OpenAirInterface (OAI). We benchmark its performance in two real-time control use cases, i.e., spectrum sharing and positioning in a 5th generation (5G) Next Generation Node Base (gNB) scenario. Our experimental results show that standardized real-time control loops via dApps are feasible, achieving average control latency below 450 microseconds and allowing optimal use of shared spectral resources.

Problem

• Real-time Control
• Intelligent Optimization
• 5G Resource Management

Innovation

• dApps
• real-time control
• 5G efficiency