w latency communications (URLLC) for large demanding applications such as vehicle-to-everything (with 1ms latency goal), and massive machine-type communications (mMTC) for multiple simultaneous connections. Even though most of these features are expected for 5G networks, B5G-specific network softwarization will make a difference [12], given by extended use of artificial intelligence and machine learning in order to enhance radio resource allocation, evolved core network functionalities, or data processing/handling and multi-agent integration, towards cognitive environments. The envisioned functional architecture of B5G/6G networks, where frequency, space and time are essential re-sources to be managed to make effective use of them [1, 2]. Worldwide, different spectrum bands have been released for 5G, with the main focus for network deployments in FR1 (i.e., under 6 GHz). However, higher- frequency spectrum, particularly 26 GHz [15, 16], is now available, and also the millimeter wave spectrum has recently become a 5G band. Nonetheless, despite the exploitation of higher frequencies and millimeter wave spectrum having been promoted to attain over gigabit data rates, the business model relying on expanding spectrum allocation is not valid for rural areas in terms of cost-effectiveness. Therefore, spectrum sharing of traditional and congested frequency bands as well as the inclusion of satellite communications will appear as solutions to avoid holding 7 Vehicular Communications in the B5G Era back those communities of a new era of connectivity [17]. In a word: 5G should work for all. Terrestrial 5G solutions under development will not follow an evolution track to allow connecting rural areas in a short horizon [12]. Basically, 5G can be primarily defined as an urban system. However, not few arguments will impel for improved B5G rural coverage [12]: urbanization, improve public safety, e-health, connected cars, and entertainment services. Before long, regulations with respect to rural coverage will arise and will be c