Smarter satellite links with AI dApps


A distributed application that runs AI inference at the network edge, co-located with the RAN, delivering decisions in under a millisecond, where traditional HARQ feedback cannot reach.

 

 

Today’s Challenge, Solution and Result

From 540 ms blind spots to 40 µs decisions.

⚠ Challenge
GEO round-trip delays of ~540 ms disable HARQ feedback, leaving the network blind to channel conditions.

āš™ Solution
A distributed AI app co-located with the RAN predicts optimal link parameters from real-time SNR and CRC inputs in under 1 ms.

āœ“ Result
50% reduction in block error rate (3.04% → 1.53%), validated end-to-end with Tier 1 partners.

10 to 100 times faster than xApps and rApps

dApps operate at the network edge with sub-millisecond control loops, far faster than near-real-time xApps or non-real-time rApps for latency-critical NTN decisions such as uplink adaptation and beam hopping.

~0.04 ms
Pure Inference Time
40 microseconds

70–90 μs
End-to-End Processing
Including I/O

~14,000/s
Sample Throughput
Per dApp Instance

dApps
<1 ms
Latency-critical edge AI
xApps
10 ms–1 s
Near-real-time RIC
rApps
>1 s
Non-real-time RIC