Slawomir Kuklinski

Ubiquitous connectivity is envisioned through the integration of terrestrial (TNs) and non-terrestrial networks (NTNs). However, NTNs face multiple routing and Quality of Service (QoS) provisioning challenges due to the mobility of network nodes. Distributed Software-Defined Networking (SDN) combined with Multi-Agent Deep Reinforcement Learning (MADRL) is widely used to introduce programmability and intelligent Traffic Engineering (TE) in TNs, yet applying DRL to NTNs is hindered by frequently changing state sizes, model scalability, and coordination issues. This paper introduces 3DQR, a novel TE framework that combines hierarchical multi-controller SDN, hierarchical MADRL based on Graph Neural Networks (GNNs), and network topology predictions for QoS path provisioning, effective load distribution, and flow rejection minimisation in future 3D networks. To enhance SDN scalability, introduced are metrics and path operations abstractions to facilitate domain agents coordination by the global agent. To the best of the authors’ knowledge, 3DQR is the first routing scheme to integrate MADRL and GNNs for optimising centralised routing and path allocation in SDN-based 3D mobile networks. The evaluations show up to a 14% reduction in flow rejection rate, a 50% improvement in traffic distribution, and effective QoS class prioritisation compared to baseline techniques. 3DQR also exhibits strong transfer capabilities, giving consistent performance gains in previously unseen environments.

Mission critical solutions are essential for providing communications and services in the case of the troubles with connectivity that are often found in infrastructure-based solutions. Such solutions are typically used in the case of disasters, lack of energy, etc. There exist several narrowband solutions that provide countrywide coverage in certain countries. In recent years, the activities related to creating mission-critical broadband solutions based on Long Term Evolution (LTE) have led to the definition of LTE Mission Critical (LTE-MC). Both solutions ignore virtualization and require dedicated mobile terminals as a part of the mission-critical communication solution. This paper describes the opportunities, open issues and a proposal of a solution that exploits Unmanned Aerial Vehicles (UAVs) and network virtualization for mission-critical services. The presented approach combines Cloud/Edge and Fog orchestration to efficiently use all the available resources, including virtualized resources of the end-user devices.

The services based on Unmanned Aerial Vehicles (UAVs) have started to be used in many countries but not on a large scale yet. The paper describes the present status of UAV services and a concept of a solution for large-scale deployment of safe and reliable UAV services that use the 5G network for communication with UAVs. Based on the Standards Developing Organizations and related industry fora activities, unmanned traffic and airspace regulations, especially the commonly supported concept of Unmanned Aircraft Systems Traffic Management (UTM), UAV-related communication requirements and 5G System (5GS) features, we have developed an alternative approach to the integration of UAV and 5GS. The proposed concept includes a set of enablers that can be provided by Mobile Network Operators in order to not only support but also leverage UAV services. As work on many items is still in progress, we identify a list of open issues and challenges and present them at the end of the paper with the main focus on the MNO–UTM provider relationship and safe flights.

In the current 5G technology domain network slicing already plays an important role as a critical enabler. An industry that 5G aims to disrupt is the vehicular one. In this paper the brief scope of the 5G‐DRIVE research project is presented, regarding 5G vehicular research between the EU and China. In the frame of 5G‐DRIVE a set of slicing mechanisms are investigated and evaluated in regard to their performance. Firstly, related to slicing mechanisms in the NFV domain the OSM orchestrator is measured in terms of scalability and performance. In the next experimental set related to RAN slicing, the Katana Slice Manager is evaluated and depicts how different slicing configurations can achieve different performance results. Furthermore, the paper showcases how 5G network slicing can be integrated as a key enabler to the stringent demands of a vehicular network environment. Finally, the paper concludes, setting future directions in the related field.

The deployment of 5G mobile networks has begun in earnest. The 5G network is built on a service-based architecture (SBA) which enables programmability of the control plane of 5G Core (5GC) and supports network slicing (NS) in both core and access networks. NS enables the creation of multiple, isolated network slices tailored for specific services with diverse KPI objectives [1]. SBA of 5GC facilitates core network user plane functions (UPF) being deployed near the network edge, which has triggered intense interest in edge activities such as Multi-access Edge Computing (MEC), whereas the traditional Self-Organizing Network (SON) functions are being enhanced continuously in 5G RAN. Meanwhile, the development of open and smart RAN led by an industry alliance, O-RAN, has received great attention. In this short paper we would like to sort out if and how all of the above would fit together in a consistent and efficient manner regarding their architecture aspects and functionalities.

Summary: Mobile network operators are currently facing a tremendous increase in the level of data traffic. Although cell size reduction is one of the most common ways used to accommodate such traffic demand, densely deployed small cells also dramatically increase the level of intercell interference. By centralizing baseband signal processing at powerful computing infrastructures, called centralized unit (CU) pools, cloud radio access network (C‐RAN) enables advanced coordination algorithms to be employed in dense small cell networks. In C‐RAN, due to stringent bandwidth and latency requirements at the fronthaul links, the optical fiber, thanks to its bandwidth and latency characteristics, continues to be the most prevalent fronthaul medium option. Nevertheless, the optical fiber is one of the fronthaul options, while C‐RAN (physical layer radio frequency [PHY‐RF] split) is one of the functional splits that can be defined each coming with different fronthaul requirements.In this paper, we formulate and solve a dynamic CU placement problem for mobile networks as an integer linear programming (ILP) problem. In the considered network, CU pools are placed at the edges of the network, and a reconfigurable millimeter wave (MMW) wireless fronthaul links are used in order to provide decentralized units (DUs) with connectivity. We study the impact of different functional splits on the placement cost and on the acceptance ratio using different substrate networks. Lastly, we propose and evaluate a CU placement heuristic algorithm using a numerical simulator. The results reveal that the optimal functional split selection can lead to significant resource utilization benefits in the RAN.

Network slicing technology will influence the way in which new networking solutions will be designed and operated. So far, network slicing is often linked with 5G networks, but this approach can be used to deploy any communications network(s) over a common infrastructure. The concept is still a subject of intensive research and standardization. From the point of view of network or service operator, it is necessary to define fundamental quantitative indicators for performance evaluation of the network slicing. Such parameters are often called Key Performance Indicators (KPIs). Network slicing KPIs should deal with network slicing run-time and life-cycle management and orchestration. The paper proposes a set of KPIs for network slicing taking into account the 5G network specifics.