t 1.5 n height in the considered vehicular scenario for each beam: (a) beam 1, (b) beam 2, (c) beam 3, (d) beam 4, (e) beam 5 at 1.5 m height (typical receiver point in a vehicular scenario), for each one of the considered beams. As it can be seen from the figures, the morphology and topology of the scenario have a high impact in the signal attenuation. In this specific case study, the tree barrier and vegetation in the middle of the road have considerable effects, due to the NLOS condition impacts that provoke the different beams. 7 Vehicular Communications in the B5G Era 7.5 Challenges Challenges in vehicular communication networks can be seen in terms of three principal perspectives. The first is the development and integration with other technologies, the second is about the main problems being addressed, and the third is about the paradigm on which the service needs to operate. Figure 7.5 shows the main issues in each of these three perspectives for the future challenges. In this manuscript, we discuss briefly some elements of these perspectives. The evolution to address all the three perspectives needs to be developed within the smart communications (SC) paradigm. Smart communications (SC) are adaptive solutions integrating signal processing techniques with networking and communications and artificial intelligence (AI) algorithms. SC generates a platform on which paradigms such as VANETs and cognitive radio networks (CRN) can evolve integrating informed decisions and resource-aware adaptation. Adaptation, reconfigurability, and learning are components to become strong future wireless communications technologies. SC will change how we deal with complex envi- ronments with massive numbers of heterogeneous devices such as in smart cities, autonomous vehicles, unmanned aerial vehicles (UAV), intelligent transportation systems (ITS), internet of vehicles (IoV), 5G, and beyond 5G (B5G). In order to provide high-quality services for these massive numbers of devices, large amounts of information need to be stored, 