Project Scope:  This project (RAIS-V2X) aims to perform an in-depth analysis of the bidirectional ultra-dense IoTN ISAC (i.e., half-duplex and full-duplex downlink and uplink) to highlight its potential and benefits. The project also aims to develop machine learning/model-based algorithms and average access designs for efficient allocation of two-way communication resources, interference management, latency reduction, and reliability improvement. Finally, the project will implement a testbed for the algorithms developed to demonstrate the proof of concept and explore the possible adaptation of these algorithms to next-generation wireless communication standards, as well as their societal and industrial applications. The three research questions to be addressed in the RAIS-V2X project are therefore the following: (1) How are ultra-dense IoTN ISACs influenced in terms of resource and interference management? (2) Is it possible to develop low-cost, energy-efficient, and hardware-efficient algorithms for ultra-dense Internet of Things (IoT) networks? And (3) can the developed algorithms be implemented in practice with hardware limitations? 

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