Guaranteed Dynamic Scheduling of Ultra-Reliable Low-Latency Traffic via Conformal Prediction

TL;DR

This paper introduces a novel URLLC scheduler that guarantees reliability and latency using conformal prediction, effectively managing traffic uncertainty in dynamic uplink scheduling.

Contribution

It proposes a new scheduling method leveraging conformal prediction to provide formal reliability and latency guarantees regardless of traffic prediction accuracy.

Findings

Guarantees reliability and latency in URLLC scheduling.

Adapts resource allocation dynamically based on conformal prediction.

Improves efficiency of resource use in uplink traffic management.

Abstract

The dynamic scheduling of ultra-reliable and low-latency traffic (URLLC) in the uplink can significantly enhance the efficiency of coexisting services, such as enhanced mobile broadband (eMBB) devices, by only allocating resources when necessary. The main challenge is posed by the uncertainty in the process of URLLC packet generation, which mandates the use of predictors for URLLC traffic in the coming frames. In practice, such prediction may overestimate or underestimate the amount of URLLC data to be generated, yielding either an excessive or an insufficient amount of resources to be pre-emptively allocated for URLLC packets. In this paper, we introduce a novel scheduler for URLLC packets that provides formal guarantees on reliability and latency irrespective of the quality of the URLLC traffic predictor. The proposed method leverages recent advances in online conformal prediction (CP), and follows the principle of dynamically adjusting the amount of allocated resources so as to meet reliability and latency requirements set by the designer.