Abstract
The applications of artificial intelligence (AI) and machine learning (ML) technologies in wireless communications have drawn significant attention recently. AI has demonstrated real success in speech understanding, image identification, and natural language processing domains, thus exhibiting its great potential in solving problems that cannot be easily modeled. AI techniques have become an enabler in wireless communications to fulfill the increasing and diverse requirements across a large range of application scenarios. In this paper, we elaborate on several typical wireless scenarios, such as channel modeling, channel decoding and signal detection, and channel coding design, in which AI plays an important role in wireless communications. Then, AI and information theory are discussed from the viewpoint of the information bottleneck. Finally, we discuss some ideas about how AI techniques can be deeply integrated with wireless communication systems.
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Jun WANG and Rong LI guided the research. Yiqun GE, Qi-fan ZHANG, and Wu-xian SHI collected the references. Rong LI, Jian WANG, and Yi-qun GE drafted the manuscript. Rong LI, Jian WANG, and Jun WANG revised and finalized the paper.
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Jun WANG, Rong LI, Jian WANG, Yi-qun GE, Qi-fan ZHANG, and Wu-xian SHI declare that they have no conflict of interest.
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Wang, J., Li, R., Wang, J. et al. Artificial intelligence and wireless communications. Front Inform Technol Electron Eng 21, 1413–1425 (2020). https://doi.org/10.1631/FITEE.1900527
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DOI: https://doi.org/10.1631/FITEE.1900527