This paper surveys Artificial Intelligence (AI) methods for acquiring and managing context-of-operation awareness of radio communication nodes, links, and networks. The meaning and significance of context information and suitability of Machine Learning (ML) methods for the enrichment of context information is discussed. A number of context features are considered in this regard and thorough analysis on which ML methods are suitable to which part of context learning is provided. The added value of the paper is the presentation of a synthesized framework of context-information processing, sharing, and management in a radio communication network by delineating a network-embedded subsystem for this management. Recommendations for a future AI/ML-based radio communication system architectures are also provided.
