Payload-size and Deadline-aware Scheduling for Upcoming 5G Networks: Experimental Validation in High-load Scenarios

TL;DR

This paper experimentally validates the PayDA scheduling algorithm in 5G networks, demonstrating its high efficiency in managing time-critical data traffic under high load conditions.

Contribution

It introduces and experimentally validates the PayDA scheduling algorithm for deadline-aware resource allocation in 5G networks.

Findings

PayDA effectively meets deadlines in high-load scenarios.

Experimental results show improved resource efficiency.

High suitability for time-critical applications in 5G.

Abstract

High data rates, low latencies, and a widespread availability are the key properties why current cellular network technologies are used for many different applications. However, the coexistence of different data traffic types in the same 4G/5G-based public mobile network results in a significant growth of interfering data traffic competing for transmission. Particularly in the context of time-critical and highly dynamic Cyber Physical Systems (CPS) and Vehicle-to-Everything (V2X) applications, the compliance with deadlines and therefore the efficient allocation of scarce mobile radio resources is of high importance. Hence, scheduling solutions are required offering a good trade-off between the compliance with deadlines and a spectrum-efficient allocation of resources in mobile networks. In this paper, we present the results of an experimental validation of the Payload-size and Deadline-aware (PayDA) scheduling algorithm using a Software-Defined Radio (SDR)-based eNodeB. The results of the experimental validation prove the high efficiency of the proposed PayDA scheduling algorithm for time-critical applications in both miscellaneous and homogeneous data traffic scenarios.