Answers are grounded in this paper and cite their sources.
With the introduction of the 5th generation of mobile communication networks (5G) and the on-going research for the 6th generation (6G), the adoption of mission critical applications is increasing, where flexible and highly reliable communication systems are needed. 5G has offered new and advanced features with a prominent example being the Ultra Reliable and Low Latency Communications (URLLC) features that can provide high reliability targets for critical applications. With this work we provide potential enhancements towards the 6G, that can provide reliability features for Enhanced Mobile Broadband (eMBB) traffic. Our proposal does not rely on any modification of the Radio Access Network (RAN) protocols or features but it provides an easy to implement solution to operators, reducing also the standardization overhead. More specifically, our proposed method can help to improve reliability of services by bounding the reported achievable throughput enabling the application to improve the overall data transmission. Specifically of importance is that our method does not require any Machine Learning (ML) technique alleviating the need for lengthy data collection processes, nor any other life-cycle management aspects. Our results are based on a realistic measurement campaign coming from a deployed network in an industrial environment. To demonstrate the effectiveness of our procedure, we compare it with a deep learning-based method for throughput prediction.
No takes yet. Share an insight, caveat, or question.
Nota et al. (2024) studied this question.