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The design of the fifth generation (5G) cellular network should take account of the emerging services with divergent quality of service requirements. For instance, a vehicle-to-everything (V2X) communication is required to facilitate the local data exchange and therefore improve the automation level in automated driving applications. In this work, we inspect the performance of two different air interfaces (i.e., LTE-Uu and PC5) which are proposed by the third generation partnership project (3GPP) to enable the V2X communication. With these two air interfaces, the V2X communication can be realized by transmitting data packets either over the network infrastructure or directly among traffic participants. In addition, the ultra-high reliability requirement in some V2X communication scenarios can not be fulfilled with any single transmission technology (i.e., either LTE-Uu or PC5). Therefore, we discuss how to efficiently apply multi-radio access technologies (multi-RAT) to improve the communication reliability. In order to exploit the multi-RAT in an efficient manner, both the independent and the coordinated transmission schemes are designed and inspected. Subsequently, the conventional uplink is also extended to the case where a base station can receive data packets through both the LTE-Uu and PC5 interfaces. Moreover, different multicast-broadcast single-frequency network (MBSFN) area mapping approaches are also proposed to improve the communication reliability in the LTE downlink. Last but not least, a system level simulator is implemented in this work. The simulation results do not only provide us insights on the performances of different technologies but also validate the effectiveness of the proposed multi-RAT scheme.
The mapping of a virtual network service onto a physical network infrastructure is a challenging task due to the joint allocation of virtual resources across nodes and links, the diverse technical requirements of end-users, the coordination between multiple host domains, and others. This issue is exacerbated further by the extension of virtualization to the next-generation radio access network (NG-RAN) architecture and the provisioning of radio access network (RAN) slicing. To that end, this article focuses on the mapping problem of the virtual network functions (VNFs), as well as their internal and external virtual links (VLs), of a RAN slice subnet onto intelligent points of presence (I-PoPs) and transport networks in the NG-RAN architecture. In this context, in contrast to the majority of the state-of-the-art proposals, which frequently fail to achieve performance objectives and neglect resource allocation constraints, this article introduces automation and intelligence at an architectural level to map VNFs and VLs onto their corresponding physical nodes and links, with the goal of achieving superior efficiency in virtual resource utilization while granting the performance of a RAN slice subnet. Benefiting from a top-down approach, the key contributions of this article are: (i) to extend the architectural framework of network slicing towards the NG-RAN architecture and provide a comprehensive overview and critical analysis of the components and functionalities of a RAN slice subnet; (ii) to integrate the Experiential Network Intelligence (ENI) framework into a joint architecture of the network functions virtualization–management and orchestration (NFV–MANO), Third Generation Partnership Project-network slicing management system (3GPP-NSMS), and I-PoPs in order to render automation and intelligence to the management and orchestration aspects of a RAN slice subnet in the NG-RAN architecture; and (iii) to propose a learning-assisted architectural solution for mapping the VNFs, as well as their internal and external VLs, of a RAN slice subnet onto the underlying I-PoPs and transport networks.
The fifth-generation mobile telecommunication network is expected to support multi-access edge computing (MEC), which intends to distribute computation tasks and services from the central cloud to the edge clouds. Toward ultra-responsive, ultra-reliable, and ultra-low-latency MEC services, the current mobile network security architecture should enable a more decentralized approach for authentication and authorization processes. This paper proposes a novel decentralized authentication architecture that supports flexible and low-cost local authentication with the awareness of context information of network elements such as user equipment and virtual network functions. Based on a Markov model for backhaul link quality as well as a random walk mobility model with mixed mobility classes and traffic scenarios, numerical simulations have demonstrated that the proposed approach is able to achieve a flexible balance between the network operating cost and the MEC reliability.
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor positioning.. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and 5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and Wi-Fi positioning techniques for indoor localization.