  The research in the sixth generation of communication 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 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 communications,
instead of hard coded communications, can be learned for more efficient task
execution and communication resources use. Moreover, new physics phenomenon
should be exploited such as the thermodynamics of communication as well as the
the interaction between information theory and electromagnetism to better
understand the physical limitations of different technologies, e.g, holographic
communications. Another new communication paradigm is to consider the
end-to-end approach 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 twelve
scientific challenges for rebuilding the theoretical foundations of
communications, and we overview each of the challenges while providing research
opportunities and open questions for the research community.
