The OCUDU dApp Platform: An Open Runtime and E3 Interface for Real-Time AI-RAN
Machine learning has shown its largest gains in the band below 10 ms inside a 3GPP new radio (NR) 5G distributed unit (DU): link adaptation, per-slot scheduling, channel estimation, and the receiver itself. No open platform has let independently built software run there. Prior dApp frameworks reached the band only as external observers of an export stream. This paper is a guided introduction to the OCUDU dApp platform, an open runtime and E3 interface under which signed AI-RAN applications execute inside a production DU under three timing contracts: resident on the GPU receive chain (Class A), inside the scheduler's 100 us admitted deadline (Class B), or as never-blocking observers whose ...
| Authors | Timothy O'Shea, Matthew Pennybacker, Andriy Kharchenko |
|---|---|
| Primary category | cs.NI |
| Published | 7 September 2026 |
| Last updated at source | 7 September 2026 |
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