The emergence of new mobile communication technologies represents a global revolution that is changing the way we interact with and learn about our environment. Effective low-cost mobile communication instigated an era of highly interconnected societies and performs as a strong driver of business innovation. However, the implementation and adoption of mobile-enabled technologies such as the Internet of Things (IoT) are met with a wide range of barriers, from physical network architectures to data analytics. One of the current challenges in this field is the design of novel intelligent approaches for integrating, operating and managing large-scale intelligent indoor mobile (ii-mobile) networks.

Network management and control solutions are fundamental mobile communication requirements to manage complexity, provide scalability, preserve users’ privacy and guarantee usability. It is of vital importance to study ii-mobile communications as this sector makes up more than half the total IoT market value. Most of the significant technical challenges hindering effective operation of mobile systems are mainly found in three areas: in indoor deployment, this includes intelligent interoperability where devices coming from different vendors need to interoperate to achieve common goals; in intelligent set-up and management for which ii-mobile network systems are often managed by novice IT users who own the system, thus systems must be able to self-recover from failures quickly and cost-effectively; and in intelligent spectrum sharing for which ii-mobile communications are commonly characterised by low power local area networking (LPLAN) technologies. LPLAN technologies operate in the overcrowded 2.4GHz unlicensed band creating a challenge to achieve reliable short-range communications in high levels of interference.

This Special Issue focuses on intelligent indoor mobile communication technologies that support large-scale applications with special emphasis on narrowband technologies suitable for massive connectivity of low-cost devices. We welcome original research and review articles focusing on indoor communication technology, machine learning including deep learning and federated learning, blockchain, and other new technologies to solve the massive connection and data challenges in indoor communication systems.

Potential topics include but are not limited to the following:

• Machine learning for indoor communication systems
• Development of intelligent indoor technologies
• Signal processing techniques for secrecy in multi-antenna mobile systems
• Antenna/node selection and cooperation in large-scale ii-mobile networks
• Resource allocation in indoor communication systems
• Traffic offloading in indoor communication systems
• Communication protocols, technologies, and security for large-scale networks
• Network architectures for adaptive network operation and management
• Data analytics and data-driven business models for indoor mobile communications
• Distributed detection, estimation and inference in large-scale ii-mobile network operation and management
• ii-mobile communication/radio simulation tools
• Predictive machine learning analytics and other security intelligence processes
• Indoor device localization and tracking in high-density IEEE 802.11ah networks
• Cross-layer operability at lower network levels, i.e., physical and data link layers
• Network security, management and performance through network control signaling