Intelligent communication systems have received recent interest in research due to their attractive features which include adaptability, pliability, and self-configuration. Upcoming 6G communication systems and the future wireless communication systems to follow are expected to integrate computational intelligence into wireless networks to improve the system’s robustness. Academicians and industry personnel have predicted that 6G wireless systems are massive and scalable heterogeneous networks that can be powered by computational intelligence to improve the system throughput. Ubiquitous Artificial Intelligence (U-AI) is a segment of computational intelligence that is exploited in 6G wireless communication networks. With this computational intelligence in place, the 6G system will revolutionize the data-driven market in the future.

Empowerment requires the implementation of machine learning algorithms across the heterogeneous network for data collection and processing. Security is one of the key aspects to be considered during the implementation of this technology which is taken care of by the U-AI. The U-AI preserves the privacy details of the data in the server both during the collection and processing. This Special Issue will focus on the development of novel learning algorithms for the successful implementation of the U-AI in future wireless communication systems. Traditional computational intelligence utilizes neural networks in addition to the prevailing fuzzy systems incorporating evolutionary computation. However, the implementation of U-AI will lead to privacy considerations which are addressed through novel machine learning algorithms such as federated learning. These learning algorithms are expected to maximize system performance by optimizing the network parameters. In addition to the optimization of the network parameters, the issue will also focus on the development of intelligent signal processing algorithms for channel estimation and modeling using U-AI.

The aim of this Special Issue is to discuss and disseminate the research progress made in the implementation of U-AI in wireless communication networks to resolve the security, trust, and privacy issues in 6G systems. Original research and review articles are welcomed.

Potential topics include but are not limited to the following:

• Wireless system architecture for 6G systems
• Novel learning algorithms for heterogeneous wireless systems
• Network architecture adopting U-AI
• Network management using computational intelligence
• Multiple access techniques involving intelligent computation
• Intelligent signal processing algorithms
• Security, trust, and privacy issues in 6G systems
• Channel estimation and modeling using computational intelligence
• Optimization algorithms for machine learning-based network control and decision making
• Deep learning and deep neural networks for U-AI