The IEEE Open Journal of the Communications Society (OJ-COMS) is an open access, all-electronic journal that publishes original high-quality manuscripts on advances in the state of the art of telecommunications systems and networks. The papers in IEEE OJ-COMS are included in Scopus. Submissions reporting new theoretical findings (including novel methods, concepts, and studies) and practical contributions (including experiments and development of prototypes) are welcome. Additionally, survey and tutorial articles are considered.

The IEEE Open Journal of the Communications Society covers science, technology, applications and standards for information organization, collection and transfer using electronic, optical and wireless channels and networks, including but not limited to: Systems and network architecture, control and management; Protocols, software and middleware; Quality of service, reliability and security; Modulation, detection, coding, and signaling; Switching and routing; Mobile and portable communications; Terminals and other end-user devices; Networks for content distribution and distributed computing; and Communications-based distributed resources control.

Hallmarks of the IEEE Open Journal of the Communications Society (OJ-COMS) are a rapid peer review process and open access of all published papers.  The broad scope of the journal comprises, but is not limited to:

Big Data and Machine Learning for Communications
Cloud Computing, Edge Computing, and Internet of Things
Communications and Information Security
Communications Theory and Systems
Green, Cognitive, and Intelligent Communications and Networks
Multimedia Communications
Network and Service Management
Network Science and Economics
Optical Communications and Optical Networks
Resource Management and Multiple Access
Signal Processing for Communications
Underwater Communications and Networks
Wired Communications and Networks
Wireless Communications and Networks

Special Issue on Industrial Communication Networks (ICNets) for Industry 5.0
Día de Entrega: 2024-12-31

The start of the 2010s witnessed a surge in the integration of various digital tools and technologies to create comprehensive and interconnected systems known as hyper-automation, courtesy of the fourth industrial revolution. However, in the last 3-4 years, the conventional working process in the industry has been shattered, which impacted societies globally. The industries must be sustainable and adapt to any situation, i.e., resilience. Furthermore, the trend is moving towards more personalized products and services, which compels the industries to take a more collaborative approach in comparison to hyper-automation. Industry 5.0 paves the way to the next industrial innovation cycle that aligns with the platforms compatible with the fourth iteration and addresses the importance of collaboration between machine and man, i.e., collaborative robots. Industry 4.0 laid the groundwork for human-machine collaboration through hyperconnectivity between the end user and the industrial components, such as supply chain management, logistics, and plants. The fifth iteration notches it up to integrate robotic precision with human creativity by digitally integrating the communication between both stakeholders.

Communication networks play a pivotal role in maintaining the integration and hyperconnectivity between man and machines. With the evolution of devices into systems of systems, such as the integration of the Internet of Things (IoT) and cyber-physical systems (CPS), the characteristics of networks have undergone significant changes. Industrial Communication Networks (ICNets) were introduced to handle data integrity, real-time control, large installations, and sometimes harsh operating environments inside and outside the factory floor. Examples of ICNets include ControlNet, Modbus, DeviceNet EtherCAT, EtherNet/IPProfinet, and so on. ICNets enable communication paths among PCs, controllers, and field devices, which is difficult to achieve with traditional communication networks.

To achieve complete transparency between enterprise IT networks and ICNets in the industrial plant, industrial Ethernet has been used extensively for industrial automation. In this regard, ICNets aim to meet real-time operational requirements, which are made possible if the information is handled deterministically. Currently, these networks also must be able to support the massive number of devices, which are increasingly heterogeneous and imply a need to support a wide range of standards. Furthermore, industrial networks must often offer solutions with improved reliability, greater efficiency, and faster response times, which are key characteristics of CPS-based systems. These benefits could be achieved by designing for a multi-protocol environment, opting for the best communication protocols, and urging the eco-system to take the initiative to develop interoperable and non-proprietary protocols in general, but also for energy-efficient, carbon-aware, and resilient systems. Industrial networks face additional challenges, such as an increasing volume of data, support for analytics/AI/compute across that data, and monitoring activities remotely from home, thus, realizing the smart manufacturing process in the truest sense. Additionally, they are often tasked to support low-power requirements, congestion-free communication, and seamless wireless and cellular integration with next-generation networks (NGNs). Finally, ICNets are used for various applications, such as industrial robotics, cobot communication, vision systems for anomaly detection, and automotive industries. ICNets will likely draw upon emerging technologies such as Private 5G, Network Slicing, etc. Although the associated challenges mentioned above illustrate what makes ICNets compelling, many other applications, use cases, and issues make them interesting and worthy of further exploration. Therefore, this Special Issue will seek technical, empirical, and conceptual papers that can offer practical and novel solutions concerning the following topics, but not strictly limited to:

- Security and Privacy for ICNets
- Sustainable and Resilient Zero-Touch Networks for Industrial applications
- Virtualization techniques (Metaverse and Digital Twin) for ICNets
- Network Slicing, SDN, MEC, and NFV for ICNet
- Integration of time-sensitive networking in industrial wireless networks
- Integration of wireless systems into currently deployed industrial networks
- Intelligent signal processing for reduced interference
- 3GPP Standardization for ICNets
- Integration of wireless systems into currently deployed industrial networks
- Intelligent signal processing for reduced interference
- 3GPP Standardization for ICNets
- New networking architectures, including OpenRAN for ICNets
- RF-controlled intelligent reflecting surface for ICNets
- Advance Artificial Intelligence (AI) techniques for Resilient ICNets
- Quality of Service (QoS) in ICNets, including topics such as Dynamic Resource Allocation, Spectrum Allocation, Energy and Carbon Efficiency 

Special Issue on Emerging Technologies Enhanced Cooperative Integrated Sensing and Communication in 6G Era
Día de Entrega: 2025-01-31

6G will turn the vision of everything sensing, everything interconnecting, and everything intelligent into reality. That is, the 6G network will have native sensing capability, thus making itself a huge sensor to perceive the physical world ubiquitously. Leveraging radio sensing capability, the integrated sensing and communication (ISAC) technology will utilize wireless signals to realize perception functions such as positioning, detection, imaging, and identification of targets, acquire information about the surrounding physical environment, tap communication capabilities, and enhance user experience. Through endogenous integration of spectrum resource allocation, hardware architecture design, multi-point collaboration, and all-around interaction of information, it can realize green energy saving while realizing communication and sensing capabilities, improve spectrum efficiency and detection accuracy, and ultimately realize the performance enhancement of the whole network.

By combining the advancements of other emerging technologies in the 6G era, such as artificial intelligence (AI), terahertz (THz), intelligent reflecting surface (RIS), Cell-Free, etc., cooperative ISAC relying on multiple base stations (BSs) is driven to become a reality. For instance, AI can analyze and process the perceived environmental information in real-time through methods such as machine learning and deep learning, which can realize adaptive adjustment and intelligent decision-making of multiple BSs, thus enabling efficient cooperative ISAC. Besides, the very narrow beamwidth available at the THz frequency band and Massive MIMO system can facilitate the realization of high-definition sensing and localization. In addition, RIS can provide a virtual line-of-sight (LOS) path to conquer the blockage problem and introduce additional degrees of freedom to improve both the communication and sensing ability, thus allowing multiple distributed BSs to collaborate when the direct link is blocked.

This Special Issue brings together leading research experts from industry and academia in the areas of wireless communications, signal processing, and artificial intelligence, with an emphasis on new approaches, techniques, and applications for cooperative ISAC. We solicit high-quality original research papers on topics including, but not limited to:

    Information Theory for Cooperative ISAC.
    Cooperative Structure/Protocol for Networked ISAC.
    Sensing Data Fusion for Cooperative ISAC.
    MIMO, Massive MIMO, and Intelligent Reflecting Surface (IRS) for ISAC.
    Millimeter Wave and THz Cooperative ISAC.
    AI-based Signal Processing for ISAC
    Interference Analysis and Management in Cooperative ISAC
    ISAC for Non-Terrestrial Networks (NTNs)
    Security and Privacy Issues in Networked ISAC.
    Resource Allocation and Optimization in Multi-Base Station ISAC.
    ISAC Testbed or Practical Applications with Cooperative ISAC Technology.

Special Issue on Generative AI and Large Language Models Enhanced 6G Wireless Communication and Sensing
Día de Entrega: 2025-01-31

6G combines wireless sensing and communication into a single system, enhancing both functions with limited resources. Such integration enhances the functionality of 6G systems while reducing the need for separate devices, offering wide-ranging applications in areas such as vehicular networks and intelligent healthcare. While promising, the enhancement of functions poses challenges to various technologies across different layers in the 6G system. The recent growth of user data and advancements in artificial intelligence have accelerated the development of Generative AI (GAI) technologies and large language models (LLMs). GAI technologies and LLMs hold robust data analysis, processing, and augmentation capabilities, offering strong support for various technologies in 6G. For example, LLMs can be used to analyze vast amounts of network data to predict traffic patterns, identify bottlenecks, and suggest optimizations, which can improve resource allocation, enhance throughput, and reduce latency in 6G networks.

This Special Issue aims to provide a chance for researchers from academia and industry to share the latest findings and solutions using LLMs and GAI to enhance various technologies across different layers of 6G communications and sensing. These include but are not limited to

    GAI and LLMs Assisted Radio Resource Management in 6G Communications and Sensing
    GAI and LLMs Enabled Security Enhancements in 6G Communications and Sensing
    Incentive Mechanism Design via GAI and LLMs in 6G Communications and Sensing
    GAI and LLMs for Network Optimization in 6G Communications and Sensing
    Mobile Edge Intelligence Based on GAI and LLMs for 6G Communications and Sensing
    GAI and LLMs-Based Network Architectures and Protocols for 6G Communications and Sensing
    GAI and LLMs for MIMO Designs in 6G Communications and Sensing
    GAI and LLMs Assisted Beamforming in 6G Communications and Sensing
    Testbed and Platform Development for GAI and LLMs Enabled Communications and Sensing
    GAI and LLMs-Based Signal Processing and Augmentation for 6G Communications and Sensing