is published six times per year, and is committed to publishing high quality papers that advance the state-of-the-art and practical applications of communications and information networks. JCN is indexed in Science Citation Index Expanded (SCIE), Engineering Village and Scopus. Theoretical research contributions presenting new techniques, concepts, or analyses, applied contributions reporting on experiences and experiments, and tutorial expositions of permanent reference value are welcome. The subjects covered by this journal include all topics in communication theory and techniques, communication systems, and information networks.
COMMUNICATION THEORY AND SYSTEMS
includes information theory, modulation/signal design, detection/estimation, fading/equalization, optical communications, transmission systems, access systems, synchronization, error control coding, source coding/data compression, security/cryptography, cognitive radio, compressed sensing, and network coding.
WIRELESS COMMUNICATIONS
includes mobile and portable communications systems, transmission modulation and coding for mobile terrestrial and satellite systems, multicarrier systems, cooperative communications, multi antenna/user systems, ultra-wideband communications, wireless network design and performance evaluation including traffic analysis, ad hoc and sensor networks, MAC protocols, and generally simulation or analytical evaluation of any wireless systems.
NETWORKS AND SERVICES
includes network physical and software architecture, communication protocols, network hardware and software technologies, switching and routing, multimedia techniques, Internet/Intranet protocols and services, mobility networks and protocols, operations and management, signaling and control, active networks, services and applications.
AI FOR COMMUNICATION
Encompasses artificial intelligence, machine learning, and data science techniques applied to communication theory and systems, wireless communications, networks and services. It also includes communication and network technologies that facilitate AI advancements. Relevant topics include, but are not limited to, deep learning for channel estimation and feedback, beamforming, modulation/demodulation, encoding/decoding, and error control, reinforcement learning for adaptive resource allocation and dynamic spectrum management, AI-driven secure communication, sensing, and computation for next-generation intelligent networks, data-driven approaches for intelligent routing, network optimization, and performance evaluation, semantic communication.
