Mobile communication is one of the most vibrant fields of global technological innovation. The International Telecommunication Union (ITU) released its “Framework and overall objectives of the future development of IMT for 2030 and beyond” in June 2023, defining the vision development, typical scenarios, and capability indicators of sixth-generation (6G) mobile networks. The international standardization organization 3rd Generation Partnership Project (3GPP) also initiated the formulation of their 6G Release 20 (R20) in June 2023, marking the transition of global 6G research from the conceptual discussion stage to that of technical practice. To accurately grasp 6G development trends and promote the advancement of 6G mobile networks, this special issue focuses on the latest research progress in 6G technology development, standard formulation, and engineering practice, based on our previous special issue titled 6G Requirements, Vision, and Enabling Technologies, published in 2022. The current special issue contains 13 papers.

The first paper, “AI and deep learning for terahertz ultramassive MIMO: From model-driven approaches to foundation models” by Prof. Khaled B. Letaief’s group, explores the fundamental role of artificial intelligence (AI) in addressing the challenges of computational complexity, modeling difficulty, and measurement limitations in the design of transceivers for terahertz ultra-massive multiple-input multiple-output (MIMO) systems. The article proposes three potential research directions: model-driven deep learning, channel state information-based models, and the application of large language models.

The second paper, “Explicit semantic-base-empowered communications for 6G mobile networks” by Prof. Ping Zhang’s group, proposes a semantic communication (SemCom) system that uses clear semantic bases (Sebs) as the basic units to represent semantic connotations. The article presents a mathematical model of Sebs and the SemCom architecture based on Sebs. A clear knowledge base is constructed, and the evolution of the communication system is realized, ensuring the effectiveness and compatibility of the proposed SemCom based on Sebs.

The third paper, “Generative semantic communication: Architectures, technologies, and applications” by Prof. Shuguang Cui’s group, explores the application of generative artificial intelligence (GAI) in SemCom and conducts a comprehensive study. It introduces three widely used SemCom systems supported by classical GAI models, proposes a novel generative SemCom system, and demonstrates its effectiveness. Four typical application scenarios of generative SemCom are described in detail, and three open issues for future research are discussed—namely, the deployment of large language models on resource-constrained edge devices, the dynamic evolution of AI agents at transceivers, and privacy and security concerns during transmission.

The fourth paper, “A high-fidelity and high-efficiency simulator for 6G-integrated space-ground networks” by Prof. Xuemin (Sherman) Shen’s group, presents a high-fidelity and efficient computer simulator that can design and analyze the various algorithms and protocols necessary for the operation and deployment of 6G air-ground-integrated networks. The simulator supports the development of 6G wireless communication systems with low-Earth-orbit mega-constellation satellites and overcomes the challenges introduced by the highly dynamic nature of the network topology and the scale of mega-constellation-to-constellation simulations and performance evaluations.

The fifth paper, “6G space-air-ground integrated networks for unmanned operations: Closed-loop model and task-oriented approach” by Prof. Wei Feng’s group, proposes a task-oriented framework based on radio maps that utilizes environmental and task-related information to achieve service provision for task matching. The paper also discusses open challenges and possible solutions in the development of adaptive generative neural networks with a structure similar to that of the nervous system.

The sixth paper, “A task-driven design approach for 6G AI-native architecture” by Dr. Xiaoyun Wang’s group, proposes a novel 6G AI-native architecture that combines distributed AI data and computing components with hierarchical centralized collaborative control and flexible on-demand deployment. The article also analyzes the standardized practice of the integration of mobile networks and AI and looks forward to the standardization of architecture design based on AI in 6G.

The seventh paper, “The Agentic-AI Core: An AI-empowered, mission-oriented core network for next-generation mobile telecommunications” by Dr. Wen Tong’s group, proposes a task-oriented next-generation mobile communication core network architecture driven by AI: the “Agentic-AI Core.” As an open and flexible system architecture, the Agentic-AI Core is expected to accelerate the innovation process and significantly shorten the standard release cycle.

The eighth paper, “A wideband amplifying and filtering reconfigurable intelligent surface for wireless relay” by Prof. Tie Jun Cui’s group, proposes a wideband amplifying and filtering reconfigurable intelligent surface that can enhance the in-band signal energy and filter the out-of-band signal of incident electromagnetic waves. This intelligent surface enables the miniaturization of reconfigurable intelligent surface arrays and possesses enhanced anti-interference capabilities, overcoming the problems of limited operating range and spectral interference that exist in traditional reconfigurable intelligent surfaces.

The ninth paper, “Cooperative sensing for 6G ISAC: Concept, key technologies, performance evaluation, and field trial” by Dr. Guangyi Liu’s group, introduces the application scenarios, evolution history, and four core characteristics of cooperative communication and sensing integration, proposing a general system model and evaluation framework. Through system-level simulations and field trials, the article demonstrates the practical application feasibility of the collaborative intelligent sensor network architecture, providing guidance for the future research direction of collaborative intelligent sensor networks.

The tenth paper, “A compact millimeter-wave, dual-band, dual-polarized, duplex, and scalable phased array enabling B5G/6G multi-standard systems” by Prof. Wei Hong’s group, proposes a new compact, dual-band, dual-polarized, and duplex phased-array architecture that integrates four independent beamforming systems into a single printed circuit board. This enables the proposed phased array to support concurrent, dual-band, and dual-polarization four-beam operations, providing a promising solution for beyond fifth-generation (B5G) and 6G millimeter-wave multi-standard systems.

The eleventh paper, “Generative video communications: Concepts, key technologies, and future research trends” by Prof. Wenjun Zhang’s group, introduces a new paradigm of generative video communication in video communication systems, using GAI technology to enhance the expression of video content. The article presents the key technical paths of generative video communication, including elastic encoding, collaborative transmission, and trustworthy evaluation, and explores its potential applications in task-oriented and immersive communication.

The twelfth paper, “Robot subset selection-based multi-user edge computing for swarm lifetime maximization with correlated data sources” by Prof. Rahim Tafazolli’s group, proposes a method for maximizing the lifetime of a machine group in a wireless network using a multi-user edge computing system. By selecting the appropriate robot subset to transmit its sensed data to the edge server and effectively utilizing the correlations among distributed data sources, the operational lifespan of the machine group can be extended. Comprehensive simulation experiments have been conducted to evaluate the effectiveness of the proposed method.

The thirteenth paper, “Wireless environmental information theory: A new paradigm toward 6G online and proactive environment intelligence communication” by Prof. Jianhua Zhang’s group, proposes an environment intelligence communication (EIC) architecture suitable for 6G based on the wireless environmental information theory (WEIT). Here, the WEIT is established for the first time by addressing three key questions regarding environmental information. The paper demonstrates that the proposed EIC architecture significantly outperforms the statistical paradigm in aspects such as overhead reduction, channel prediction, and performance optimization. It explores a novel and highly promising approach and discusses several open issues and challenges, including accuracy, complexity, and generalization ability.

In closing, we thank all the authors who submitted their research papers to this special issue. We also acknowledge the contributions of many experts in the field who participated in the review process and provided valuable suggestions to improve the content and presentation of these papers. Finally, we extend our sincere thanks to the members of the editorial team of Engineering for their support and help in bringing forward this special issue. We hope readers will enjoy the papers in this collection and gain inspiration regarding the key enabling technologies, standards development, and practical implementation of 6G research.