Mutual/single information theory has been the theoretical background of old and advanced communication systems. Information theory has shown innovative directions for future breakthroughs at each critical evolution stage of mobile communication generation. Modern wireless communications revolve around infinitely more complicated topologies, which often include multiple users, fluctuating channel strengths, and nodes that cooperate or compete. The network’s size increases proportionately, and the information transmission becomes more complex. The applications of AI and ML technologies in wireless communications have drawn significant attention recently in information theory. AI has demonstrated tangible success in speech understanding, image identification, and natural language processing domains, thus exhibiting its great potential in solving problems that cannot be easily modelled. AI techniques have become an enabler in wireless communications to fulfil the increasing and diverse requirements across an extensive range of application scenarios in modern 5G/6G networks. There are several typical wireless scenarios, such as channel modelling, channel decoding and signal detection, and channel coding design, in which AI, ML and deep neural networks play an important role in wireless communications.
This special issue aims to encourage researchers to present original and recent developments inn information theory to analyze what lies in 5G/6G networks. It focuses on the fundamental theory, performance limits, design, and management issues in 5G/6G communication systems. For this purpose, comprehensive overviews and surveys for future networks and original papers related to these techniques are proposed. This issue is composed of 6 outstanding contributions.
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