1. [Publications](/publications)
2. AI-RAN: Transforming RAN with AI-driven Computing Infrastructure
 
 # AI-RAN: Transforming RAN with AI-driven Computing Infrastructure 

  ![Publication image](/sites/default/files/styles/wide/public/default_images/default.jpeg?itok=qUFsuJCP "Publication image")

 The radio access network (RAN) landscape is undergoing a transformative shift from traditional, communication-centric infrastructures towards converged compute-communication platforms. This article introduces AIRAN which integrates both RAN and artificial intelligence (AI) workloads on the same infrastructure. By doing so, AI-RAN not only meets the performance demands of future networks but also improves asset utilization. We begin by examining how RANs have evolved beyond mobile broadband towards AI-RAN and articulating manifestations of AI-RAN into three forms: AI-forRAN, AI-on-RAN, and AI-and-RAN. Next, we identify the key requirements and enablers for the convergence of communication and computing in AI-RAN. We then provide a reference architecture for advancing AI-RAN from concept to practice. To illustrate the practical potential of AI-RAN, we present a proof-ofconcept that concurrently processes RAN and AI workloads utilizing NVIDIA Grace-Hopper GH200 servers. Finally, we conclude the article by outlining future work directions to guide further developments of AI-RAN.



 ## Authors



Lopamudra Kundu (NVIDIA)

Xingqin Lin (NVIDIA)

Rajesh Gadiyar (NVIDIA)

Jean-Francois Lacasse (NVIDIA)

Shuvo Chowdhury (NVIDIA)

 

 

 ## Publication Date



Wednesday, January 15, 2025

 

 ## Published in



[IEEE Network](https://ieeexplore.ieee.org/document/11141658)

 

 ## Research Area



[Telecommunications](/research-area/telecommunications)

 

 

 ## External Links



[Paper](https://arxiv.org/pdf/2501.09007)