6G networks: Beyond Shannon towards semantic and goal-oriented communications

The goal of this paper is to promote the idea that including semantic and goal-oriented aspects in future 6G
networks can produce a significant leap forward in terms of system effectiveness and sustainability. Semantic
communication goes beyond the common Shannon paradigm of guaranteeing the correct reception of each
single transmitted bit, irrespective of the meaning conveyed by the transmitted bits. The idea is that, whenever
communication occurs to convey meaning or to accomplish a goal, what really matters is the impact that the
received bits have on the interpretation of the meaning intended by the transmitter or on the accomplishment
of a common goal. Focusing on semantic and goal-oriented aspects, and possibly combining them, helps to
identify the relevant information, i.e. the information strictly necessary to recover the meaning intended by the
transmitter or to accomplish a goal. Combining knowledge representation and reasoning tools with machine
learning algorithms paves the way to build semantic learning strategies enabling current machine learning
algorithms to achieve better interpretation capabilities and contrast adversarial attacks. 6G semantic networks
can bring semantic learning mechanisms at the edge of the network and, at the same time, semantic learning
can help 6G networks to improve their efficiency and sustainability.