The IEEE Transactions on Cognitive Communications and Networking (TCCN) is committed to timely publishing of high-quality manuscripts that advance the state-of-the-art of cognitive communications and networking research. The focus of the Transactions will be on “cognitive” behaviors in all aspects of communications and network control, from the PHY functions (including hardware) through the applications (including architecture), and in all kinds of communication networks and systems regardless of type of traffic, transmission media, operating environment, or capabilities of communicating devices. IEEE TCCN will welcome papers dealing with the design, analysis, evaluation, experimentation and testing of cognitive communications and network systems. Inter-disciplinary approaches are encouraged. Papers that focus on experimental infrastructures or tools for cognitive communications and networking will also be considered, provided that they contain significant original contributions in the communications or networking areas.

Since the term “cognitive” may be interpreted in multiple ways, we define here a cognitive entity as one that is capable of selecting and carrying out actions depending on its own goals and its perception of the world and that may also be capable of learning from experience by interacting with the world. Thus, a cognitive entity means an intelligent entity which possesses the following basic components: perception, learning/reasoning and decision making. Papers that will be considered for publication in the IEEE Transactions on Cognitive Communications and Networking must BOTH explicitly include approaches related to the “intelligent entity” AND provide original contributions on communications or networking.

Topics of interest include (but are not limited to):

    Machine learning and artificial intelligence for communications and networking
    Distributed learning, reasoning and optimization for communications and networking
    Architecture, protocols, cross-layer, and cognition cycle design for intelligent communications and networking
    Information/communications theory and network science for intelligent communications and networking
    Ontologies, languages, and knowledge representation for intelligent communications and networking
    Security and privacy issues in intelligent communications and networking
    Cognitive radio and dynamic spectrum access
    Cognitive technologies supporting software-defined radios, systems and networks
    Emerging services and applications enabled by intelligent communications and networks

Special issues will form an integral part of IEEE TCCN. Guest editorial teams are welcome to propose special issues on new emerging areas in cognitive and intelligent communications and networking. Please contact the Editor-in-Chief if you are interested in submitting a proposal.

Co-Sponsors: IEEE Computer Society and IEEE Signal Society Processing

Special Issue on TCCN SI 2024 : Generative AI for Next-Generation Networks and Communication: Challenges and Solutions
截稿日期: 2024-07-01

IEEE Transactions on Cognitive Communications and Networking (TCCN)
Special Issue on
Generative AI for Next-Generation Networks and Communication: Challenges and Solutions


In the dynamic landscape of communication networks, traditional Artificial Intelligence (AI) algorithms have been instrumental, optimizing and troubleshooting functions within communication networks. Beyond this, artificial intelligence holds the potential for computers or robots to command systems, empowering network operators to strategically plan, execute, and manage services in response to evolving consumer demands. Artificial intelligence aids operators by providing precise predictions without actual implementations. It facilitates process automation, enhancing efficiency while minimizing operating costs. However, as we approach the Sixth Generation of Mobile Networks (6G) with heightened demands for connectivity, capacity, data rates, latency, mobility, and reliability, the limitations of these traditional AI models become evident.

Recent breakthroughs in Generative Artificial Intelligence (GAI), such as transformer-based models like Generative Pretrained Transformers (GPTs), signify a paradigm shift in AI. GPT-3.5 and GPT-4 showcase the ability to support customization and data generation, introducing a new dimension to communication networks with dynamic adaptation. GAI's applications span text summarizers, language translators, chatbots, and tools for upskilling. GAI's impact on content creation is transformative, promising enhanced efficiency and personalized experiences in various fields. Integrating GAI into next-generation networks and communication redefines interactions, communication, and information access. GAI's lifelike speech and language generation elevate virtual assistants and chatbots. GAI revolutionizes network performance through data analysis, learning patterns, and predicting traffic dynamics, thereby enhancing resource allocation efficiency and reducing latency. This transformative approach ensures elevated quality of service, increased network capacity, and improved user experiences. GAI's applications empower intelligent decision-making in network planning, optimize infrastructure deployment, and contribute to context-aware services, dynamically adapting to users' needs. As GAI becomes integral, it catalyzes innovation, promising heightened efficiency, adaptability, and personalized user experiences in the evolving communication landscape.

Despite the transformative potential of GAI in next-generation networks and communication, seamless integration faces specific challenges. One significant hurdle is the optimization of GAI algorithms to handle large-scale data processing and communication tasks efficiently. Another challenge lies in ensuring the adaptability of GAI systems to dynamic network environments, addressing issues of scalability and real-time responsiveness. Addressing these challenges is pivotal for unlocking the full potential of GAI in shaping the future of intelligent communication networks. Therefore, this special issue aims to offer a platform for researchers from both academia and industry to publish recent research findings and to discuss opportunities, challenges, and solutions related to GAI. In particular, this Special Issue solicits original research papers about state-of-the-art approaches, methodologies, and technologies enabling efficient and practical GAI towards the realization of next-generation networks and communication. Potential topics of interest include but are not limited to the following:

GAI-based Resource Management for Next-Generation Networks and Communication
GAI-assisted Network Planning and Deploying for Next-Generation Networks
GAI-enable Mobile Computation Offloading over Next-Generation Networks and Communication
GAI-based Semantic Communication for Next-Generation Networks and Communication
GAI for Digital Twining in Next-Generation Networks and Communication
GAI-based Distributed Learning Communication for Next-Generation Networks and Communication
GAI-enable Security and Privacy Provisioning in Next-Generation Networks and Communication
GAI-based Content and Model Cache Management for Next-Generation Networks and Communication
GAI-empowered Applications for Next-Generation Networks and Communication
Quality of Service (QoS) Improvement of GAI in Next-Generation Networks and Communication
GAI-based Optimization and Acceleration Techniques for AIGC services over Next-Generation Networks
Large Model Frameworks and Techniques for GAI for Optimization
Comprehensive Performance Evaluation of GAI in Next-Generation Networks and Communication
Experimental Prototyping and Testbeds of GAI over Next-Generation Networks and Communication


Submission Guidelines
Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Cognitive Communications and Networking guidelines. Note that the page limit is the same as that of regular papers. Please submit your papers through the online system and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. If requested, abstracts should be sent by e-mail directly to the Guest Editors.


Important Dates
Manuscript Submission: 1 July 2024
First Review Round: 1 October 2024
Revision Papers Due: 15 November 2024
Acceptance Notification: 30 December 2024
Final Manuscript Due: 30 January 2025
Publication: 2025


Guest Editors
Xiaofei Wang
Tianjin University, China

Dusit (Tao) Niyato
Nanyang Technological University, Singapore

Jiawen Kang
Guangdong University of Technology, China

Christos Verikoukis
University of Patras, Greece

Zehui Xiong
Singapore University of Technology and Design, Singapore

Elisa Bertino
Purdue University, USA