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Recent advances in Vehicle-to-Everything (V2X) technology and the upcomingsixth-generation (6G) network will dawn a new era for vehicular services withenhanced communication capabilities. Connected and Autonomous Vehicles (CAVs)are expected to deliver a new transportation experience, increasing the safetyand efficiency of road networks. The use of millimeter-wave (mmW) frequenciesguarantees a huge amount of bandwidth (> 1GHz) and a high data rate (>10Gbit/s), which are required for CAVs applications. However, high frequency isimpaired by severe path loss, and line of sight (LoS) propagation can be easilyblocked by static and dynamic obstacles. Several solutions are beinginvestigated, and the most promising one exploits relays. However, traditionalrelay schemes react to link failure and leverage instantaneous information,which impedes efficient relay selection in highly mobile and complex networks,such as vehicular scenarios. In this context, we propose a novel proactiverelaying strategy that exploits the cooperation between CAVs and environmentinformation to predict the dynamic LoS-map, which describes the links'evolution in time. The proactive relaying schemes exploit the dynamic LoS-mapto maximize the network connectivity. A novel framework integrating realisticmobility patterns and geometric channel propagation models is proposed toanalyze the performance in different scenarios. Numerical simulations suggestthat the proactive relaying schemes mitigate beam blockage and maximize theaverage probability of connecting CAVs with reliable links.

LoS-Map Construction for Proactive Relay of Opportunity Selection in 6G V2X Systems