3D-O-RAN: Dynamic Data Driven Open Radio Access Network Systems

Abstract

A method of generating a deep neural network (DNN) may comprise receiving one or more application-level requirements associated with network communications, translating the one or more application-level requirements into one or more technical constraints, and providing the one or more technical constraints to a control loop that generates a certified DNN architecture based on the technical constraints. The control loop may further comprise a DNN search engine and a hardware synthesis engine. The method may comprise selecting, using the DNN search engine, a candidate DNN architecture based on the technical constraints, and generating, using the hardware synthesis engine, a hardware architecture corresponding to the selected candidate DNN architecture. The technical constraints may comprise one or more of (i) network latency, (ii) available hardware resources, (iii) available software resources, (iv) required DNN accuracy, (iv) computation and/or network slicing allocation, and (v) current noise and/or interference levels at the DNN input.

Dependencies are inferred from the claim text.