The management of a 5G system comprises Operation and Management aspects defined by 3GPP, including Network Slicing, and the Management and Orchestration aspects specified in ETSI's Network Function Virtualization framework. Our Proof-of-Concept demonstrates the implementation of an on-demand provisioning procedure of a Network Slice Subnet composed of Virtual Network Functions from potentially different vendors. The demonstration includes a Network Management System conforming to the 3GPP Service-Based Management Architecture, an ETSI MANO orchestrator, and a Network Function Virtualization Infrastructure.

The era of 5G broadband wireless networks is inextricably connected with the provision of high data rates to mobile users, as well as bandwidth demanding and low latency applications. While large scale deployments of 5G Public Networks are ongoing, enterprises are interested to deploy their own 5G Non Public Networks (NPNs), customized to better serve their specific use cases. To this end, the goal of this paper is to present an architectural approach for cost-efficient 5G Standalone NPN deployment, leveraging cell densification, disaggregated RAN with open interfaces, edge computing and AI/ML-based network optimization. For this purpose, open solutions, such as O-RAN and MANO frameworks for cloud native micro-service deployments are adopted. Furthermore, research, development and deployment challenges are also discussed.

While a growing number of Internet of Things (IoT) applications require reliable mechanisms to determine the precise location of remote devices, the aspects regarding the security of positioning algorithms should not be neglected. In this context, this paper proposes a physical-layer location verification method for IoT networks in which the concentrator node is assisted by several anchor nodes that are spread in the area of interest. We design an optimization problem to choose appropriately which anchor nodes should be triggered in the location verification process in order to minimize the activation rate of each anchor. The performance evaluation results show that the proposed policy achieves an activation rate reduction of the anchor nodes of at least 70%.