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IEEE Open Journal of the Communications Society (OJ-COMS)

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IEEE
ISSN:
2644-125X
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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. Submissions reporting new theoretical findings (including novel methods, concepts, and studies) and practical contributions (including experiments and development of prototypes) are welcome. Additionally, review and survey articles are considered; however, tutorials are not included.

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
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issues
Special Issue on Cyber Forensics for Emerging Technologies
截稿日期: 彩神8官方版-06-15

Emerging technologies, such as internet of things (IoT), cloud computing, edge computing, software-defined network (SDN) and network function virtualization (NFV), have already shown their potential to heavily impact modern life. However, the widespread adoption of those technologies is still being hindered by various serious security and privacy concerns. Moreover, the cyber forensics is another critical concern with the adoption of those modern technologies. However, due to the unique nature of these technologies and non-trivial challenges in offering security and forensics solutions for them, there exist several open research problems that are critical in ensuring a safer adoption to the modern era to provide better security guarantee and ensure proper forensics procedure. This special issue on cyber forensics for emerging technologies aims to provide a platform for researchers and practitioners to publish novel solutions to ensure better protection in emerging technologies. This section invites submissions on new attacks and solutions on emerging technologies (e.g., IoT, cloud/edge computing, and SDN/NFV) that shed light on various security and forensics problems and provide their effective solutions. The topics of interests related to cyber forensics for emerging technologies include, but are not limited to: Forensics in Cloud Computing Virtual Network Security Data Protection in Clouds Trusted Computing in Clouds Cloud Security Auditing Risk Analysis for Clouds SDN Security/Forensics NFV Security/Forensics Security and Privacy of Federated Clouds and Edge Computing Security and Privacy of Fog Computing Forensics and visualization of Big Data Forensics in IoT Data Protection in IoT Malware Analysis and Attribution Digital Evidence Extraction/query using Machine Learning and Data Mining Social Networking Analysis OSINT (Open Source Intelligence) Non-Traditional Forensic Applications Distributed System Forensics Healthcare/ E-health security and forensics Submission Guidelines Submit manuscript to: http://mc.manuscriptcentral.com/oj-coms For information regarding IEEE OJ-COMS including its publication policy and fees, please visit the website http://www.comsoc.org/publications/journals/ieee-ojcoms. Lead Guest Editor Suryadipta Majumdar, University at Albany – SUNY, USA Guest Editors Prabir Bhattacharya, Concordia University, Canada Indrakshi Ray, Colorado State University, USA Ali Dehghantanha, University of Guelph, Canada Yuan Hong, Illinois Institute of Technology, USA Krishnashree Achuthan, Amrita Vishwa Vidyapeetham, India Daniel Bastos, British Telecom, UK
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Softwarization and Intelligence in Edge Computing
截稿日期: 彩神8官方版-06-20

Edge computing, by pushing the services, applications and data from the centralized cloud to the network edge, can significantly lower the service latency and hence improve the service quality experienced by the end users. Therefore, edge computing is widely regarded as an alternative or complementary solution to centralized cloud computing, with the advantages of vast distribution and user proximity. Edge computing is supposed to better support a variety of bandwidth-intensive and latency-sensitive applications such as IoT data processing, autonomous driving, healthcare applications. Edge computing imposes a convergence trend that all resources, e.g., sensing, communication, computation, and storage, shall be managed in a joint manner. A more flexible resource management approach is thus called for. Fortunately, recent developments in various technologies like programmable sensors, software-defined networking (SDN), network function virtualization (NFV), and container are engineering toward a softwarization trend in edge computing. These technologies together “soften” the system such that system administrators can flexibly and jointly manage all the resources in edge computing, other than relying on previously built-in rules or policies. Meanwhile, recent advances in artificial intelligence (AI) also have inspired the trend of applying AI technologies in the management of edge computing. The openness and flexibility resulted from the softwarization are readying edge computing to be empowered by various AI technologies. At the initial stage in this trend, there are still many open challenges to be tackled. For example, we need to consider how to integrate various AI technologies with these softwarization technologies, which target at different aspects, or even with different management granularities and interfaces. On the other hand, many different AI technologies with different characteristics and capabilities are available options. We first need to understand how to appropriately adopt the right technology for a specific problem, and how these technologies perform in comparison with traditional policy-based methods. Moreover, AI technologies usually adopt a data-driven system management approach. How to choose the appropriate data for analysis and mining becomes a critical issue. At the same time, when talking about the adoption of AI technologies, other than simply applying the intelligent technologies, we shall also customize these technologies according to the problem characteristics. To this end, this special issue will be focusing on various problems in applying AI technologies to embrace the softwarization trend in edge computing. We also welcome works on related technologies, such as machine learning, microservice, next-generation networking, network security, IoT, vehicular networks, and big data. Possible topics of interest include but are not limited to: Software defined technologies in edge computing Intelligent flow scheduling in SDN-managed edge computing Reinforcement learning for edge computing management Microservice management in edge computing Interplay of container and next-generation networking technologies in edge computing Edge service access pattern mining and analysis Intelligent networking for edge computing Intelligent security framework and protocol for edge computing Intelligent privacy protection in edge computing Intelligent edge computing for healthcare Intelligent edge computing for industrial applications Protocols and standardization for edge computing Emerging technologies on machine learning for edge computing Novel intelligent edge computing architecture and frameworks Testbed, prototype of intelligent edge computing Performance evaluation and analysis of intelligent edge computing Submission Guidelines Submit manuscript to: http://mc.manuscriptcentral.com/oj-coms For information regarding IEEE OJ-COMS including its publication policy and fees, please visit the website http://www.comsoc.org/publications/journals/ieee-ojcoms Lead Guest Editor Deze Zeng, China彩神网官网 University of Geosciences, Wuhan, China彩神网官网 Guest Editors Celimuge Wu, The University of Electro-Communications, Japan Md Zakirul Alam Bhuiyan, Fordham University, NY, USA Shui Yu, University of Technology Sydney, Australia Rajendra Akerkar, Western Norway Research Institute, Norway Nirwan Ansari, New Jersey Institute of Technology, USA
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Edge Intelligence for Immersive Communications
截稿日期: 彩神8官方版-06-30

With the explosive growth of smart devices and development of wireless technology, numerous new applications such as Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), autonomous driving and intelligent manufactory enter our daily life and put stringent requirements on the current communications technologies. Boosted by multimedia applications and Internet-of-Things (IoT), immersive communications is considered to bring a novel vision on the development of advanced communications systems and networks. Nevertheless, to fully explore the immersive experience and applications, ultra-reliable, low latency and high data rate communications systems are required. However, the conventional access network can hardly accommodate such stringent requirements, due to limited capacity and long latency on the backhaul links. Novel approaches that bring various network functions and contents to the network edge, i.e., mobile edge computing and caching, are promising to tackle the aforementioned challenges. On the other hand, there are various open issues on improving the capability of mobile edge computing and caching. The addressing of these challenges requires complicated network optimization methods, and often needs online adaptation with respect to the volatile network states, which the conventional model-based optimization can hardly tackle. In this regard, machine learning approaches can provide valuable ingredients and potentially efficient solutions. These are also able to help revisit the elementary wireless network techniques like scheduling and transmission, specifically in the era of wireless edge intelligence. Moreover, cross-discipline research not only means optimizing the wireless communications via machine leaning, but can also reveal how wireless can assist the artificial intelligence (AI)-based applications. This is vital, as AI can be a key traffic contributor in the future, and such a topic has been rarely touched upon in recent studies. Future natural and effective immersive experiences will be created by drawing upon intertwined research areas including multimedia communications, machine learning, signal processing, computer vision, wireless networking, sensors, displays and sound reproduction systems, where edge Intelligence will play a significant role. This special issue aims to consolidate the current state-of-the art in terms of fundamental research ideas and network engineering, geared towards exploiting wireless edge intelligence for providing immersive communications that requires low latency access to computing resources, such as AR/VR/MR, connected autonomous driving, massive IoT, smart grid, intelligent manufactory, and others. The topics of interests related to edge intelligence for immersive communications include, but are not limited to: System modelling: Computation modelling, content modelling, energy consumption modelling Novel transmission technologies for learning-based applications at the network edge Scheduling schemes for efficient training, inference for edge learning/edge AI Timely data acquisition mechanisms to support delay sensitive edge processing Coded computing for edge intelligence Enabling technologies, e.g., SDN, NFV, CRAN, D2D, cloud/fog computing and networking Emerging applications via edge intelligence: vehicular networking, massive IoT, smart grid, healthcare, intelligent manufactory Novel network architecture: convergence of computing, communications and caching, content/information-centric network, cognitive computing and networking, big data analytics Context-aware schemes: incentive mechanism for computing and caching, pricing, game theoretic approach, network economics, caching placement and delivery Mobility management for mobile edge computing and proactive caching, the way to exploit the mobility for more computing and caching opportunities Energy efficiency aspects: energy harvesting, energy storage, energy transfer AR/VR applications Tactile internet Security and privacy issues Prototyping, test-beds and field trials Submission Guidelines Submit manuscript to: http://mc.manuscriptcentral.com/oj-coms For information regarding IEEE OJ-COMS including its publication policy and fees, please visit the website http://www.comsoc.org/publications/journals/ieee-ojcoms Lead Guest Editor Zheng Chang, University of Jyväskylä, Finland Guest Editors Xiaojiang Du, Temple University, USA Zhu Han, University of Houston, USA Geyong Min, University of Exeter, UK Zhiwei Zhao, University of Electronic Science and Technology of China彩神网官网, China彩神网官网, Di Zhang, Huawei, China彩神网官网
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Machine Learning for Optical Communications and Networking
截稿日期: 彩神8官方版-07-01

Machine Learning (ML) has become a main hot topic in current years, since it covers an extremely vast area of human knowledge: from technology to economics, marketing, physics, weather forecasting, speech/image recognition, gaming, and others. In each of these applications, when an optimal decision has to be made in complex problems, ML stands out as a powerful and alternative method to solve or even to formulate such problems. In particular, in the general field of networking, and more specifically in optical networking, ML has become a dominant area of research, and scientific studies, projects and publications that are adopting this technique are rapidly increasing. All forms of ML (supervised, unsupervised, reinforcement) have been usefully applied in various contexts, from photonic transmission in the physical layer, to the control plane and IT-TLC integration, in the application layer. This special issue aims at hosting original, unpublished, and breakthrough concepts on optical communications and networking, that make use of ML as a tool to solve complex problems. The topics of interest include, but are not limited to: Photonic transmission and physical layer impairments Monitoring, fault detection and restoration Predictive maintenance Traffic prediction Network planning and optimization Traffic prediction and classification Quantum cryptography Optimal resource allocation in SDN/NFV optical networks Edge and fog computing Optical wide and metro -area network management C-RAN optimization Optical front-haul and back-haul supporting 5G /6G ML in wireless optical communications This SI will host contributed papers and one invited paper. All papers have to be novel and present unpublished results. Extended papers derived from previously-published conference papers will be accepted. A limited number of survey-type papers will be accepted. Submission Guidelines Submit manuscript to: http://mc.manuscriptcentral.com/oj-coms For information regarding IEEE OJ-COMS including its publication policy and fees, please visit the website http://www.comsoc.org/publications/journals/ieee-ojcoms Lead Guest Editor Guido Maier, Politecnico di Milano, Milan, Italy Guest Editors José Alberto Hernández, Universidad Carlos III de Madrid, Spain Zuqing Zhu, University of Science and Technology of China彩神网官网 (USTC), Hefei, China彩神网官网 Jason Jue , The University of Texas at Dallas, Richardson, TX, USA
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Software-Defined Networking and Network Function Virtualization with Artificial Intelligence
截稿日期: 彩神8官方版-07-15

Internet of Things (IoT) is a great paradigm for continuous research and development. Studies in this area focus on enabling objects to communicate with each other and to send information about their environment, facilitating decision-making and improving the Quality of Service (QoS). Likewise, the disruption of the IoT has led to the search for strategies that would mitigate the data load in complex communications networks, where data are generated, processed and exchanged among millions of sensors and devices. One of those strategies is Edge Computing (EC), which aims to prevent the congestion caused by the lack of computing resources, network or storage. This trend brings computational and service infrastructures closer to the end user by migrating data filtering, processing or storage from the cloud to the edge of the network. Nevertheless, the number of Internet-connected devices is already huge, and it continues to increase. Moreover, new and more advanced applications are developed every day, which require better QoS and therefore, greater demands in terms of bandwidth, latency and data integrity. This has fostered the emergence of new approaches that optimize the use of the resources of existing networks and make network investments profitable. Network Function Virtualization (NFV) is among these solutions and has been designed to virtualize the different components of the network. NFV is closely associated with and complementary to the concept of Software-Defined Network (SDN), Software-Defined Wireless Networks (SDWNs) and Software-Defined Wireless Sensor Networks (SDWSNs). The use of Artificial Intelligence (AI) techniques, such as Machine Learning (ML) or Deep Learning (DL), is ideal in SDN and VFN network architectures, since they enable the creation of intelligent algorithms that learn automatically in both Edge and Cloud, allocating network resources according to the needs of the users and the targeted QoS. This special issue aims to consolidate the current state-of-the art and to promote the exchange of innovative ML concepts and solutions applied to SDN and NFV in EC and IoT scenarios, focusing on the different possibilities offered by ML, such as its ability to allocate resources according to the quality of service. The topics of interests include, but are not limited to: SDN and NFV in IoT and Edge Computing scenarios Software-Defined Wireless Networks (SDWNs) and Software-Defined Wireless Sensor Networks (SDWSNs) SDN and NFV in Industrial Internet of Things SDN and NFV in the Internet of Vehicles New architectures in the field of Edge Computing, Fog Computing and Cloud Computing in IoT applications Intelligent algorithms for network resource management and orchestration from the control layer Intelligent mechanisms for the transfer of models from the Cloud to the Edge, as well as training of these models in the Edge Consensus Algorithms for Resource Allocation in Software Defined Networks New architectures for the implementation of Edge-IoT solutions with low energy consumption. Blockchain and other Distributed Ledger Technologies as NFV New case studies and applications of Edge-IoT architectures, including Industry 4.0, Smart Farming, Smart Cities, healthcare, Smart Energy, etc. Prototyping, test-beds and case-studies for SDN and NFV Reviews and surveys for SDN and NFV Submission Guidelines Submit manuscript to: http://mc.manuscriptcentral.com/oj-coms For information regarding IEEE OJ-COMS including its publication policy and fees, please visit the website http://www.comsoc.org/publications/journals/ieee-ojcoms Lead Guest Editor Antonio Skarmeta, University of Murcia, Spain Guest Editors Joel J. P. C. Rodrigues, Federal University of Piauí (UFPI), Brazil; Instituto de Telecomunicações, Portugal Sofiène Affes, INRS, Montréal, QC, Canada Yuan Shen, Tsinghua University, Beijing, China彩神网官网 Ian Oppermann, NSW Data Analytics Centre, Sydney, NSW, Australia Roberto Casado, University of Salamanca, Spain Ricardo S. Alonso, University of Salamanca, Spain
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Non-Orthogonal Multiple Access for 5G and Beyond
截稿日期: 彩神8官方版-08-01

IEEE Open Journal of Communications Society (OJ-COMS) invites manuscript submissions in the area of non-orthogonal multiple access (NOMA) for 5G and beyond. Future wireless networks are expected to meet the unprecedented requirements: higher spectral-energy efficiency, massive connectivity, ultra-reliability and low latency. Recently, non-orthogonal multiple access (NOMA) has been envisioned as one of the key enabling techniques to fulfil these demanding requirements. In contrast to the conventional orthogonal multiple access (OMA) schemes, NOMA introduces a paradigm shift in accessing networks. The fundamental concept of NOMA is to remove orthogonality in between the allocated resource blocks to different users and serve multiple users simultaneously by sharing those limited system resources. In fact, this non-orthogonal concept is a generalized framework of recently proposed different multiple access schemes for 5G and beyond wireless networks such as power-domain NOMA, sparse code multiple access, lattice partition multiple access, multi-user shared access, and pattern division multiple access. Furthermore, NOMA principles have been considered in the development of a number of standards including multi-user superposition transmission (MUST) in 3GPP LTE Advanced and layered division multiplexing (LDM) in the next generation digital TV standard. Without any doubt, this novel technique has attracted a great deal of research interest from both academia and industry. This special issue will provide a platform to bring together the latest research developments, key ideas, novel solutions to address challenging issues in NOMA which will bridge the gap in theory and practice while tailoring NOMA to incorporate in the disruptive technologies for 5G and beyond 5G (B5G) wireless networks. Prospective authors are invited to submit original manuscripts on topics including, but not limited to: Information theoretic limits and performance analysis of NOMA Transceiver design for NOMA Advanced design of channel coding and modulation for NOMA MIMO techniques for NOMA Cooperative NOMA NOMA for massive MIMO and cell-free massive MIMO Novel resource allocation techniques for NOMA Interference management in multi-cell NOMA NOMA assisted wireless caching and mobile edge computing Artificial intelligence driven techniques for NOMA Energy efficient designs for NOMA Security provisioning in NOMA Cross-layer design and optimization for NOMA Hybrid multiple access with NOMA NOMA for unmanned aerial vehicles (UAV) NOMA for Terahertz communications NOMA with other disruptive technologies for 5G and beyond wireless networks Reconfigurable intelligent surfaces and meta-surfaces for NOMA Emerging applications of NOMA Hardware implementations of NOMA Submission Guidelines Prospective authors should submit their manuscripts following the IEEE OJ-COMMS guidelines at http://www.comsoc.org/publications/journals/ieee-ojcoms. Authors should submit manuscript to: http://mc.manuscriptcentral.com/oj-coms Lead Guest Editor Kanapathippillai Cumanan, The University of York, UK Guest Editors Daniel Benevides da Costa, Federal University of Ceara (UFC), Brazil Derrick Wing Kwan Ng, The University of New South Wales, Australia George C. Alexandropoulos, National and Kapodistrian University of Athens, Greece Jie Tang, South China彩神网官网 University of Technology, China彩神网官网 Mojtaba Vaezi, Villanova University, USA Zhiguo Ding, The University of Manchester, UK
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Reconfigurable Intelligent Surface-Based Communications for 6G Wireless Networks
截稿日期: 彩神8官方版-09-01

IEEE Open Journal of Communications Society (OJ-COMS) invites manuscript submissions in the area of reconfigurable intelligent surface-based communications for the 6th generation (6G) wireless networks. The future 6G communications looks exciting with the potential new use cases and challenging requirements. However, one thing has become certain to academia and industry members in the 5G standardization process: there is no single enabling technology in the physical layer (PHY) that can support diverse 5G application requirements. Within this perspective, extensive research has already started on 6G wireless technologies. Although a plethora of modern PHY solutions have been introduced in the last few decades, it is undeniable that a level of saturation has been reached in terms of adapted modulation/coding solutions and accordingly the maximum capacity. In other words, innovative research on finding both spectrum and energy efficient techniques with low hardware cost is still imperative for realizing a sustainable wireless network evolution with scalable cost in the future. Since the beginning of the modern era of wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which generally degrades the quality of the received signal due to the uncontrollable interactions of the transmitted radio waves with the surrounding objects. However, this common belief has been changed by the recent advent of reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), large intelligent surfaces (LISs), smart mirrors, programmable wireless environments (PWEs), hypersurfaces (HSFs) etc., which enables the proactive control of the scattering, reflection, and refraction characteristics of the radio waves, by overcoming the negative effects of natural wireless propagation. Recent results have revealed that RISs can effectively enable novel and effective functionalities including wave absorption, tunable anomalous reflection, and reflection phase modification, which makes it as a potential candidate for 6G to overcome the inherent drawbacks of legacy wireless systems. This special issue aims to capture the most recent and promising research advances on the analysis, design, simulation, modeling, and implementation of RIS-assisted wireless networks, and to provide new research directions in this emerging field of research. The topics of interest include, but are not limited to Design and modeling of RIS-assisted communication systems Fundamental performance limits of RIS-assisted wireless networks Experimental results and real-time implementation of RISs Machine/deep learning (ML/DL) based solutions for RIS-assisted communication systems Channel estimation for RIS-assisted communication systems Transmission protocol design/optimization for RIS-assisted wireless networks Resource allocation and interference management with non-ideal and practical RIS models RIS-assisted multi-user and non-orthogonal multiple access systems RIS-assisted physical layer security and cognitive radio/spectrum sharing solutions Radio localization with RISs Deployment and network planning of RIS-empowered wireless networks Application of RISs for massive MIMO, millimeter wave and TeraHertz communication systems Integration of RISs to unmanned aerial vehicles (UAVs), simultaneous wireless information and power transfer (SWIPT) systems, and vehicular communications Submission Guidelines Submit manuscript to Manuscript Central. For information regarding IEEE OJ-COMS including its publication policy and fees, please visit the website. Lead Guest Editor Ertugrul Basar, Koç University, Turkey Guest Editors Ian F. Akyildiz, Georgia Institute of Technology, USA Emil Björnson, Linköping University, Sweden Linglong Dai, Tsinghua University, China彩神网官网 Andreas Pitsillides, University of Cyprus, Cyprus Qingqing Wu, National University of Singapore, Singapore
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Aerial Wireless Networks: Drones for Communications and Communications for Drones
截稿日期: 彩神8官方版-09-01

Unmanned aerial vehicles (UAVs), commonly referred to as drones, have received growing attention for their versatility and applicability to a number of domains: in surveillance systems, aerial photography, traffic control, agriculture, and even for parcel delivery and future urban transportation services, e.g., aerial taxi. To allow unmanned operation, reliable and secure service delivery, UAVs need to be connected exploiting a communication infrastructure based on robust, low latency, energy efficient transmission technology. Additionally, their use is particularly beneficial for the provision of remote connectivity or to offer emergency/disaster connectivity. Drones can also be deployed to assist terrestrial communication networks (cellular radio networks) acting as flying base stations or gateways to increase coverage and/or capacity. Radio communications play a key role in both scenarios, i.e., in communication networks for drones, and in drones for communication networks. While there exists a body of literature that reports results from the analysis, integration and experimentation of existing radio communication technology, fundamental studies and optimal design are still missing. This special issue seeks contributions of fundamental nature that assess the challenge of optimal design of the physical and media access control layers, the characterization of the communication media, the study of channel capacity and energy efficiency, the development of routing and self-organization mechanisms in both drone-assisted networks and in networks for drones. In addition, contributions related to novel radio localization techniques in support of drone navigation, as well as drone-assisted radio positioning solutions, are encouraged. The topics of interest include, but are not limited to: Fundamental performance analysis of drone-assisted terrestrial radio networks Fundamental performance analysis of radio communications for drone networks Channel characterization and modeling of drone radio networks Transmission technology and physical layer design of drone radio networks Resource management for network-connected drones Interference management for drone networks Energy efficient, ultra-reliable, low latency radio techniques Energy-aware or energy-constrained aerial network design Energy-aware or energy-constrained trajectory optimization in drone aided communication networks Path planning and coordination under energy and communication constraints in networks of drones Media access control of drone-assisted terrestrial radio networks Media access control of radio communication systems for drone networks Networking, routing and self-organization in drone-assisted networks and in networks for drones Radio localization for drone networks Drone-assisted radio localization systems Experimental results and field-tests of aerial wireless networks Submission Guidelines Prospective authors should submit their manuscripts following the IEEE OJ-COMMS guidelines. Authors should submit manuscript to Manuscript Central. Lead Guest Editor Andrea M. Tonello, University of Klagenfurt, Austria Guest Editors Marco Levorato, University of California, Irvine, USA Christos Masouros, University College彩神网app London, UK Constantinos Papadias, Athens Information Technology, Greece Yong Zeng, Southeast University, China彩神网官网
最后更新 Dou Sun 在 彩神8官方版-05-07
Special Issue on Full-Duplex Transceivers for Future Networks: Theory and Techniques
截稿日期: 彩神8官方版-10-01

IEEE OJ-COMS invites manuscript submissions in the area of Full-Duplex Communication Systems (both wired and wireless). Conventional wireless communication systems operate in half-duplex mode, i.e., current radios cannot transmit and receive at the same time and on the same frequency. Full-duplex (FD) wireless operation was generally assumed to be impossible due to the great difference in transmit and receive signal power levels. However, recent advances in antenna, hardware, and signal processing techniques have shown that FD operation is practically feasible. Thanks to novel combinations of antenna, analog, and digital cancellation techniques, self-interference (SI) suppression of 80-110 dB can be made possible. The feasibility in building a practical full-duplex radio using off-the-self hardware and software radios therefore alleviates many problems in wireless network design. While the vivid FD research continues soaring at its flat peak of popularity, the opportunity for innovation and research in FD radio remains tremendous. The FD capability is as important also in wired communications when aiming at realizing cables’ two-way capacity to the maximum. In fact, historically, FD capability has already been adopted in digital subscriber line (DSL) systems/standards in the form of echo cancellation decades before the research on wireless FD systems started. Thus, there is no question about the overall feasibility of FD wired networking, but interesting new research problems and innovation opportunities emerge from developing FD transceiver hardware, signal processing and networking concepts to outperform their half-duplex counterparts optimally in terms of different objectives and under varying design constraints. Recently, echo cancellation and FD operation were introduced into data over cable service interface specification (DOCSIS). This enables new architectures in cable network systems such as distributed access architecture (DAA) along with new access schemes like full duplex, dynamic spectrum split between upstream and downstream, and guard band elimination. FD communication in DOCSIS and DSL wired systems provides symmetric data rate and low latency to enable heterogeneous communication architecture that combines wired backhaul network with wireless access. This Special Issue solicits papers that provide novel contributions to the theory and practice of echo/self-interference cancellation and FD operation, targeting a broad range of physical and MAC layer issues as well as important applications of FD operation in future wireless and wired network designs. The topics of interest include, but are not limited to: Advanced full-duplex antenna and antenna array designs Advanced full-duplex transceiver designs (both wired and wireless) Experimental evaluation of FD transceivers and networks (both wired and wireless) Advanced self-interference/echo cancellation techniques Modelling of self-interference/echo and channel measurements in wireless and wired systems Massive MIMO and mmWave full-duplex transceiver design Performance analysis of FD transceivers, systems, and networks (both wired and wireless) Interference cancellation in full-duplex multi-user systems Non-orthogonal multiple access (NOMA) in full-duplex systems Full-duplex and self-interference cancellation techniques based on deep learning/machine learning applications Physical layer security and full-duplex techniques Full-duplex relaying and cooperative communications UAV communications with FD radios Full-duplex techniques with wireless power and energy harvesting Full-duplex device-to-device and M2M communications Full-duplex small cell deployments and heterogeneous networks Ultra-reliable low-latency communications and MAC and routing protocols with FD radios Cross-layer design, virtualization and wireless caching with full-duplex operation Echo cancellation in cable systems and hybrid fiber-coaxial architectures Submission Guidelines Submit manuscript to Manuscript Central. For information regarding IEEE OJ-COMS including its publication policy and fees, please visit the website. Lead Guest Editor Nghi Tran, University of Akron, USA Guest Editors Himal A. Suraweera, University of Peradeniya, Sri Lanka Taneli Riihonen, Tampere University, Finland Negar Reiskarimian, Massachusetts Institute of Technology, USA Hardik Jain, GenXComm Inc., USA Robert Schober, Friedrich-Alexander University of Erlangen-Nuremberg, Germany For inquiries regarding this Special Issue, please contact nghi.tran@彩神8官方版uakron.edu.
最后更新 Dou Sun 在 彩神8官方版-05-07
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