Raja Sattiraju received his Bachelors degree in ‘Mechanical Engineering’ from Jawaharlal Nehru Technological University, India in 2008. Upon his graduation, he enrolled in the first batch of the newly created Master program ‘Commercial Vehicle Technology’ and received his Masters degree in 2012 from the University of Kaiserslautern, Germany. Since then, he has been working as a researcher at the Institute of Wireless Communication and Navigation at University of Kaiserslautern under Professor Hans D. Schotten.
His key research interests include Reliable and low latency Communications for Vehicular Networking, Co-ordinated driving concepts for increased traffic efficiency, Road and Network co-simulation and applications of Machine Learning in radio communication. Other research interests include: Ranging and Localization and Autonomous vehicles.
AI-assisted PHY technologies for 6G and beyond wireless networks
Machine Learning (ML) and Artificial Intelligence (AI) have become alternative approaches in wireless networks beside conventional approaches such as model based solution concepts. Whereas traditional design concepts include the modelling of the behaviour of the underlying processes, AI based approaches allow to design network functions by learning from input data which is supposed to get mapped to specific outputs (training). Additionally, new input/output relations can be learnt during the deployment phase of the function (online learning) and make AI based solutions flexible, in order to react to new situations. Especially, new introduced use cases such as Ultra Reliable Low Latency Communication (URLLC) and Massive Machine Type Communications (MMTC) in 5G make this approach necessary, as the network complexity is further enhanced compared to networks mainly designed for human driven traffic (4G, 5G xMBB). The focus of this paper is to illustrate exemplary applications of AI techniques at the Physical Layer (PHY) of future wireless systems and therefore they can be seen as candidate technologies for e.g. 6G systems.