Kamal Deep Singh

TL;DR: A Deep Learning based model is introduced to intelligently detect the user environment, using supervised and semi-supervised multi-output classification, and relevant multi-class schemes are proposed to efficiently regroup the multiple environment categories in more than two classes.

TL;DR: Results show that the profiling of UE’s speed with fine granularity or on multiple ranges can be achieved with high accuracy on real data measured in heterogeneous deployments for 5G networks.

TL;DR: In this article, the authors propose a one-to-many negotiation mechanism allowing the provider to undertake satisfaction management: to meet fine-grained user QoE goals, while still minimizing the costs.

TL;DR: The goal of F-Interop is to extend FIRE+ with online interoperability and performance test tools supporting emerging IoT-related technologies from research to standardization and to market launch for the benefit of researchers, product development by SME, and standardization processes.