In this article, we introduce Wireless 2.0, the future generation of wireless communication networks, in which the radio environment becomes controllable and intelligent by leveraging the emerging technologies of reconfigurable metasurfaces (RMSs) and artificial intelligence (AI). In particular, we emphasize AI-based computational methods and commence with an overview of the concept of intelligent radio environments (IREs) based on RMSs. Then, we elaborate on data management aspects, the requirements of supervised learning by examples, and the paradigm of reinforcement learning to learn by acting. Finally, we highlight numerous open challenges and research directions.
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Gacanin et al. (2020) studied this question.
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