Millimeter-Wave Beam-Formed Array Antenna for Connected Driving Scenarios

Abstract

Connected vehicles are the next frontier in massive mobile communications. The automotive industry is pursuing the exchange of essential information between vehicles, road infrastructure and all kind of external agents (V2X) for improving safety and traffic efficiency. Sharing data such as the position or kinematics, for example, can be used by other road participants to make a better prediction of hazardous situations. Even though, to meet the automotive-grade requirements, such as reliability during information exchange, or to support highly-automated applications such as platooning, high levels of reliability during information exchange are required. These cannot be sustained by the sub-6 GHz V2X band so it is therefore necessary to relocate to other bands such as the millimeter- Wave (mmWave) Frequency Range 2 (FR2) band, where larger bandwidths are available. The goal of this project is to develop a mmWave beam-formed array antenna for connected driving scenarios. With this framework, it will be possible to obtain metrics and understand how channel measurements can be used to improve V2X communications, by using for instance, di?erent antenna setups or combining di?erent beamforming strategies i.e. beam steering or beam shaping in diverse down-scaled urban scenarios. Based on this, it is largely intended to use physical layer measurements as a promising first barrier to improve the quality of V2X communications. MmWave communications for advanced connected and automated vehicle driving scenarios have drawn significant attention for their adaptability in a wide variety of applications. However, when Line-Of-Sight (LOS) and link stability cannot be assured in urban scenarios, the exchange of information between two vehicles becomes more complex and sometimes even dangerous if the information sent through the channel is not reliable. In this thesis, an improved mmWave beamforming method based on array antenna beam steering is presented. By using a channel-aware imaging algorithm, it aims to solve in large part the above-mentioned problematic by finding the most reliable path in non Line-Of- Sight (NLOS) scenarios. Thus, link stability over road infrastructures might be potentially improved besides enhancing safe-channel communications and traffic efficiency.