Artificial intelligence and data-driven networks will be integral part of 6G systems. In this
article, we comprehensively discuss implementation challenges and need for architectural …

In this work, we investigate user equipment (UE) positioning assisted by deep learning (DL)
in 5G and beyond networks. As compared to state of the art positioning algorithms used in …

In modern radio networks with large antenna arrays and precise beamforming techniques,
accurate user positioning plays a key role in enabling seamless mobility management, link …

Outdoor user equipment (DE) localisation has attracted a significant amount of attention due
to its importance in many location-based services. Typically, in rural and open areas, global …

User equipment (UE) positioning accuracy is of paramount importance in current and future
communications standard. However, traditional methods tend to perform poorly in non line of …

In urban environments, cellular network-based positioning of user equipment (ue) is a
challenging task, especially in frequently occurring non-line-of-sight (nlos) conditions. This …

Deep learning (DL) methods have been shown to improve the performance of several use
cases for the fifth-generation (5G) New radio (NR) air interface. In this paper we investigate …

In the 4G era, cellular positioning was used for emergency services and services associated
to lawful interception. In 5G, commercial use cases have gained momentum and use cases …

Deep learning (DL) methods have been recently proposed for user equipment (UE)
localization in wireless communication networks, based on the channel state information …

Determining the position of ourselves or our assets has always been important to humans.
Technology has helped us, from sextants to outdoor global positioning systems, but real …