Smart City Gnosys
Smart city article details
| Title | Applications Of Machine Learning And 5G New Radio Vehicle-To-Everything Communication In Smart Cities |
|---|---|
| ID_Doc | 10106 |
| Authors | Raj R.; Kumar A.; Mandloi A.; Pal R. |
| Year | 2024 |
| Published | Signals and Communication Technology, Part F1293 |
| DOI | http://dx.doi.org/10.1007/978-3-031-34601-9_5 |
| Abstract | The process of the development of smart cities is already progressing. Smart city development can be divided into several classifications, such as smart parking, smart rendezvous points, smart healthcare facilities, smart traffic control, smart communications, smart crime control, etc. Smart traffic control and smart communication are the target areas of discussion for this chapter. These two areas together form a network of vehicles and other transportation units, along with infrastructure units, to not only provide safety on the roads but also take care of the infotainment services. As the traffic on roads is increasing rapidly, the need to use intelligent solutions from Industry 3.0 became a must. One major solution is to let the vehicles communicate with each other. Researchers have been working on vehicular ad hoc networks for over a decade. In the recent past, researchers released Release 16, which focused on the development of Fifth-Generation New Radio Vehicle-to-Everything Communication (5G NR V2X). The goal is to use the resources in such a way that the advantages of millimeter-wave communication are fully exploited. This chapter describes vehicular ad hoc networks, LTE-V2X communications, and 5G NR V2X communication, among other topics. Some problems are there with the 5G NR V2X communications, such as the initial access problem, higher attenuation of millimeter waves, non-line-of-sight communication, etc. This chapter presents a detailed description of these problems and their probable solutions. Further, with the recent Industry 4.0 advancements in the areas of artificial intelligence and machine learning, optimal solutions to the above problems can be found. This chapter also discusses the methods of machine learning that are used or can be used in the solutions to the problems of 5G NR V2X communications. Each issue of 5G NR V2X communication is discussed in detail, along with the probable solutions with or without the use of machine learning algorithms. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
| Author Keywords | 5G NR V2X; Beamforming; Initial access; Machine learning; Relay vehicle selection; Resource allocation; Smart cities |
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