5G New Radio (NR) is touted as a pivotal enabling technology for the genuine realization of connected and cooperative autonomous driving. Despite numerous research efforts in recent years, a systematic overview on the role of 5G NR in future connected autonomous communication networks is missing. To fill this gap and to spark more future research, this paper introduces the technology components of 5G NR and discusses the evolution from existing cellular vehicle-to-everything (V2X) technology towards NR-V2X. We primarily focus on the key features and functionalities of physical layer, Sidelink communication and its resource allocation, architecture flexibility, security and privacy mechanisms, and precise positioning techniques. Moreover, we envisage and highlight the potential of machine learning for further performance enhancement in NR-V2X services. Lastly, we show how 5G NR can be configured to support advanced V2X use cases.

No abstract

No abstract

No abstract

In this paper, we propose and study a context-aware leader selection algorithm within the concept of mobile clouds. We deploy a dedicated Cooperative Control Server (CCS) to assist and manage the process of leader selection more efficiently. The proposed algorithm collects data regarding instantaneous conditions of Mobile Terminals (MTs) and their radio environment; and then computes and assigns a rank to each MT. The ranks calculated based on a combination of different contextrelated parameters and corresponding weighting factors, allow selecting the leader. Furthermore, the energy efficiency and stability of the selected leaders is investigated for different parameter values through simulations. The results indicate that the proposed algorithm can achieve great energy saving in cooperative scenarios through proper leader selection.