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The research in the sixth generation of wireless networks needs to tackle new challenges in order to meet the requirements of emerging applications in terms of high data rate, low latency, high reliability, and massive connectivity. To this end, the entire communication chain needs to be optimized, including the channel and the surrounding environment, as it is no longer sufficient to control the transmitter and/or the receiver only. Investigating large intelligent surfaces, ultra-massive multiple-input-multiple-output, and smart constructive environments will ultimately contribute to this direction. In addition, to allow the exchange of high dimensional sensing data between connected intelligent devices, semantic and goal-oriented communications need to be considered for a more efficient and context-aware information encoding. In particular, for multi-agent systems, where agents are collaborating together to achieve a complex task, emergent communication, instead of hard-coded communication, can be learned for more efficient task execution and communication resources use. Moreover, new physical phenomena, such as the thermodynamics of communication and the interaction between information theory and electromagnetism should be exploited to better understand the physical limitations of different technologies, e.g., holographic communications. Another new communication paradigm is to consider the end-to-end communication system optimization instead of block-by-block optimization, which requires exploiting machine learning theory, non-linear signal processing theory, and non-coherent communications theory. Within this context, we identify and investigate twelve scientific challenges for rebuilding the theoretical foundation of communications. Furthermore, we present an overview of each of the challenges, along with their respective research opportunities and associated challenges.
Chafii et al. (Sun,) studied this question.