Mission Critical Sensors and Sensor Networks (MC-SSN)

Submission Deadline: 30 October 2019

IEEE Access invites manuscript submissions in the area of Mission Critical Sensors and Sensor Networks (MC-SSN).

MC-SSN have been applied to missions such as battlefield, border patrol, search and rescue, critical structure monitoring and surveillance, etc. To support critical missions, sensors and sensor networks will need to be flexible and interactive, and still work despite limited bandwidth, intermittent connectivity and with a large number of devices on the network. Sometimes, humans will be the elements within mission critical sensors and sensor networks that are most vulnerable to deception, and humans will be handicapped when they are concerned that information they are receiving via the network is untrustworthy, even if that concern is misplaced. For example, the military can take all kinds of measures to counterattack cyberattacks on sensor networks, including injecting fake code meant to attract and catch intruders, using disposable connected devices, large-scale physical fingerprinting and ongoing physical and information probing of networks. The military will also need to look at the “psychosocial behaviors” of attackers and see if they can discern patterns of behavior.

In MC-SSN, the advantages of linking multiple electronic support measures and electronic attack assets to achieve improved capabilities across a networked mission-critical force have yet to be quantified. Algorithms are sought for fused, and/or, coherent cross-platform Radio Frequency (RF) sensing. The MC-SSN algorithms should be capable of utilizing RF returns from multiple aspects in time-coordinated sensors and sensor networks. Such adaptation, management and re-organization of information sources, devices, and networks must be accomplished almost entirely autonomously, in order to avoid imposing additional burdens on humans, and without much reliance on support and maintenance services. Moreover, humans, under extreme cognitive and physical stress, will be strongly challenged by the massive complexity of the MC-SSN and the information it will produce and carry. Advances in technologies that capitalize on the benefits of the MC-SSN will have to assist humans in making useful sense of this massive, complex, confusing, and potentially deceptive ocean of information, while taking into account the ever-changing mission.  New approaches and low-complexity algorithms are expected to enable MC-SSN to automatically manage and effect risk and uncertainty in a highly deceptive, mixed cooperative/adversarial, information-centric environment. All of these challenges demand new theories of (and methods for) sensor design, networking, sensing, information management, and decision support analytics. The goal of the Special Section in IEEE Access is to publish the most recent (unclassified) results in MC-SSN.

The topics of interest include, but are not limited to:

  • Overcoming Bandwidth limitation in MC-SSN
  • Intermittent connectivity modeling in MC-SSN
  • Massive devices management in MC-SSN
  • Cybersecurity in MC-SSN
  • Density and deployment of the MC-SSN
  • Heterogeneous modality selection in MC-SSN
  • Information fusion in MC-SSN
  • Capacity of MC-SSN
  • Reliable communications in MC-SSN
  • Target detection in MC-SSN
  • Dynamic resource allocation in MC-SSN
  • Adapt MC-SSN local and distributed processing
  • Waveform design and adaptation in MC-SSN
  • Decision making with uncertainties in MC-SSN
  • Human in the loop for MC-SSN
  • Machine learning for MC-SSN
  • Situation understanding based on MC-SSN
  • Threat assessment based on MC-SSN
  • New and nontraditional sensors in MC-SSN

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Qilian Liang, University of Texas at Arlington, USA

Guest Editors:

  1. Tariq S. Durrani, University of Strathclyde, UK
  2. Jing Liang, University of Electronic Science and Technology, China
  3. Jinhwan Koh, Gyeongsang National University, Korea
  4. Yonghui Li, University of Sydney, Australia
  5. Xin Wang, Qualcomm Inc, USA

 

Relevant IEEE Access Special Sections:

  1. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things
  2. Networks of Unmanned Aerial Vehicles: Wireless Communications, Applications, Control and Modelling
  3. Underwater Wireless Communications and Networking

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: liang@uta.edu

Towards Service-Centric Internet of Things (IoT): From Modeling to Practice

Submission Deadline: 31 October 2018

IEEE Access invites manuscript submissions in the area of Towards Service-Centric Internet of Things (IoT): From Modeling to Practice

The Internet of Things (IoT) refers to an emerging paradigm, to seamlessly and ubiquitously integrate a large number of smart things with intra/inter links to the physical and cyber worlds. The sensor enabled communication technologies are connecting billions of things, by efficiently utilizing their locations in the real world. It has brought active participation and tangible creation of benefits to the economy and ultimately the society. As the so-called smart things are extremely diverse and heterogeneous in terms of computing and communication technology and resource capability, there is no stand-alone solution towards realization of service-centric provisioning in IoT. The service domain in IoT environments is also diverse including energy efficiency, computing capability, coordination time, resource harvesting capacity, dimension of things, etc. The growing diversity enforces the necessity to address the most significant issue of technological complexity, for practical enhancement and evaluation of quality of service (QoS) and quality of experience (QoE) for service-oriented use cases in IoT environments.

The literature has vastly contributed towards architecture design for cooperative communication, computing and application-centric development. However, the efforts towards realistic modeling and evaluation of QoS and QoE in IoT environments have not witnessed enough attention in academia and industrial research labs. Although the realistic implementations of IoT environments have been realized in various domains including product engineering, marketing, health, sports, and security, the scalability of these implementations is not guaranteed due to the lack of QoS and QoE evaluation in IoT environments. The R&D towards service-centric technologies in IoT environments will support the mass realization of realistic IoT implementations resulting in effective economic and social benefits. Driven by the enhancement of QoS and QoE for diverse use cases in IoT, new technologies are keen to the rise of spanning different service-centric aspects in IoT environments.

The aim of this Special Section in IEEE Access is to provide opportunities for researchers and practitioners to publish their latest and innovative contributions with new methodologies and modeling techniques towards service-centric IoT framework. Theoretical investigation and prototype implementation-based studies are particularly welcomed, as IEEE Access attracts practical articles discussing new experiments or measurement techniques and interesting solutions to engineering, including negative results. The topics of interest include, but are not limited to:

  • Standardization progress in service-centric IoT
  • Business model driven network services management in service-centric IoT
  • Resource management and scheduling for service-centric IoT
  • Energy and resource efficiency in service-centric IoT
  • Location accuracy enhancements for service-centric IoT
  • Cloud and edge computing for massive service-centric IoT applications
  • New waveforms and frame structures for massive IoT connection
  • High-reliability-low-latency tactile communications for IoT
  • Coverage extension with resource constrained sensors
  • Enhancing privacy, security and trust for service-centric IoT

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Yue Cao, Northumbria University, UK

Guest Editors:

  1. Omprakash Kaiwartya, Northumbria University, UK
  2. Xiaodong Xu, Beijing University of Posts and Telecommunications, China
  3. William Liu, Auckland University of Technology, New Zealand
  4. Jaime Lloret, Polytechnic University of Valencia, Spain
  5. Yuanwei Liu, Queen Mary University of London, UK
  6. Yuan Zhuang, Bluvision Inc., USA

 

Relevant IEEE Access Special Sections:

  1. Intelligent Systems for the Internet of Things
  2. Multimedia Analysis for Internet-of-Things
  3. Cyber-Physical-Social Computing and Networking

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: yue.cao@northumbria.ac.uk

Theory, Algorithms, and Applications of Sparse Recovery

Submission Deadline: 31 December 2018

IEEE Access invites manuscript submissions in the area of Theory, Algorithms, and Applications of Sparse Recovery.

Sparse recovery is a fundamental problem in the fields of compressed sensing, signal de-noising, statistical model selection, and more. The key idea of sparse recovery lies in that a suitably high dimensional sparse signal can be inferred from very few linear observations. Recent years have witnessed a great development of the sparse recovery theory and fruitful applications in the general field of information processing, including communications channel estimation, dictionary leaning, data compression, optical imaging, machine learning etc. Extensions to the recovery of low-rank matrices and higher order tensors from incomplete linear information have also been developed, and remarkable achievements have been achieved.

This Special Section is devoted to both the current state-of-the-art advances and new theory, algorithms and applications of sparse recovery, with the goals to highlight new achievements and developments, and to feature outstanding open issues and promising new directions and extensions, on the theory, algorithms, and applications. Both survey papers and papers of original contributions that enhance the existing body of sparse recovery are also highly encouraged. The topics of interest include, but are not limited to:

  • Fundamental limit of sparse recovery algorithms
  • Sparse recovery with phase-less sampling matrices
  • Trade-off between sparse recovery effectiveness and efficiency
  • Greedy methods for phase-less sparse recovery
  • Design and optimization for deterministic sampling matrices
  • Theory/algorithm/applications of sparse signal recovery
  • Theory/algorithm/applications of low-rank matrix recovery
  • Theory /algorithm/applications of tensor recovery
  • Efficient hardware implementation of sparse recovery algorithms
  • Sparse recovery for machine learning problems

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Jinming Wen, University of Toronto, Canada

Guest Editors:

  1. Jian Wang, Fudan University, China
  2. Bo Li, Nuance Communication, Canada
  3. Xin Yuan, Nokia Bell Labs, USA
  4. Kezhi Li, Imperial College London, UK

 

Relevant IEEE Access Special Sections:

  1. Advances in Channel Coding for 5G and Beyond
  2. Trends, Perspectives and Prospects of Machine Learning Applied to Biomedical Systems in  Internet of Medical Things
  3. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: jinming.wen@mail.mcgill.ca

Big Data Learning and Discovery

Submission Deadline: 01 October 2018

IEEE Access invites manuscript submissions in the area of Big Data Learning and Discovery.

We are now witnessing a dramatic growth of heterogeneous data, consisting of a complex set of cross-media content, such as text, images, videos, audio, graphics, spatio-temporal data, multivariate time series, and so on. The inception of informatics has offered very robust and hi-tech solutions for data and information analysis, collection, storage and organization, as well as product and service delivery to the customers. Recently, technological advancements, particularly in the form of Big Data, have resulted in the storage of enormous amounts of potentially valuable data in a wide variety of formats. This situation is creating new challenges for the development of effective algorithms and frameworks to meet the requirements of big data representation and analysis, knowledge understanding and discovery. Computer vision, for example, has a huge potential in many aspects for automated understanding of big data and has been used successfully to speed up and improve applications such as large-scale image segmentation, object detection, object tracking, event modeling, scene parsing, 3D reconstruction, image classification and retrieval and so on. Moreover, deep learning has revolutionized diverse key areas, such as speech recognition, object detection, image classification, and machine translation, with the data-driven representation learning. Therefore, it is now necessary to explore advanced theories and techniques for heterogeneous big data learning and discovery. This includes theory related to: data acquisition, feature representation, time series analysis, knowledge understanding, data-based modeling, dimension reduction, semantic modeling and the novel and promising big data analytic research direction, e.g. image/video captioning, affection computing, multimedia storytelling, Internet commerce, healthcare, earth system, communications, augmented/virtual reality and elsewhere.

This Special Section in IEEE Access invites contributions from diverse research fields, such as deep learning, feature extraction and fusion, big data indexing and retrieval, complex network analysis of time series (big data), brain-computer interface and EEG data analysis, healthcare big data analysis, ocean observing data mining, etc…

The topics of interest include, but are not limited to:

  • Architecture design for big data processing pipeline
  • Multi-modal and diverse big data collection
  • Complex network analysis of time series (big data)
  • Time series analysis and its applications
  • Deep learning methodology and its applications
  • Brain-computer interface and EEG data analysis
  • Benchmark for specific big data applications
  • Big data indexing and retrieval
  • Robust feature extraction for heterogeneous big data representation
  • Robust similarity measure and learning
  • Multi-modal and multi-view feature fusion and selection
  • Deep Learning for big data discovery
  • Multi-task/Transfer learning for big data understanding
  • Domain Adaptation for big data prediction
  • Optimal design of the underwater vehicles based on the big ocean observing data
  • Ocean observing data mining from underwater vehicles
  • Earth observing system data analysis
  • Real-world applications based on big data learning
  • Survey papers with regards to topics of big data learning and discovery
  • Big data learning for developing new prediction schemes and their applications to neuroscience, climatology, finances, infrastructure and cyberattacks etc.
  • Deep learning methodology for understanding of tipping points in large complex systems

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Zhong-Ke Gao, Tianjin University, China

Guest Editors:

  1. An-An Liu, Tianjin University, China
  2. Yan-Hui Wang, Tianjin University, China
  3. Michael Small, The University of Western Australia, Australia
  4. Xiaojun Chang, Carnegie Mellon University, USA
  5. Jürgen Kurths, Potsdam Institute for Climate Impact Research, Humboldt University, Germany

 

Relevant IEEE Access Special Sections:

  1. Healthcare Big Data
  2. Real-Time Edge Analytics for Big Data in Internet of Things
  3. Advanced Signal Processing Methods in Medical Imaging

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: zhongkegao@tju.edu.cn

Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things

Submission Deadline: 31 May 2019

IEEE Access invites manuscript submissions in the area of Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things.

Internet of things (IoT) which supports ubiquitous information exchange and content sharing among smart devices with little or no human intervention is a key enabler for various applications such as smart city, smart grid, smart health, intelligent transportation systems, and so on. With the evolutionary growth of IoT, it is estimated that almost 50 billion devices will be interconnected by 2020. The gap between the rapidly growing demands of data rate and existing bandwidth-limited network infrastructures has become ever prominent. As a novel communication model, information-center networking (ICN) is different from traditional IP address-centric model. In fact, ICN develops from host-to-host to host-to-network, which is a promising architecture to improve the performances of IoT. Therefore, how to explore the inherent nature of the large amount of devices, such as smart caching, communications, computing and cybersecurity capabilities, to build up an efficient and smart information-centric IoT (IC-IoT) paradigm is of great significance.

Together with recent advances in caching, communication, computing, and cybersecurity, a novel smart technical paradigm for IC-IoT is emerging. Communication refers to content-driven wireless technologies and networking protocols that guarantee end-to-end connectivity. Caching and computing refer to the capabilities of the IC-IoT devices to store the data, and execute the edge computing tasks locally. Cybersecurity means to secure and protect the privacy of the content generated from or stored at IC-IoT devices. Fully utilizing all these features can complement the current study of IC-IoT and overcome the current limitations of such a highly distributed network.  However, effectively utilizing these existing capabilities for addressing the fundamental challenges in IC-IoT remains nontrivial. Despite the development of IoT, some fundamental problems are still open and require immediate studies, such as:

  • How can we achieve much higher energy and spectrum efficiency of the IC-IoT network with limited bandwidth provisioning?
  • How can we utilize storage and caching capabilities of IC-IoT devices to offload the data in order to release the traffic of the cellular networks and provide low-latency services?
  • Can we leverage recent advances in computing to evaluate the needs for locally computing or offloading to cloud/edge?
  • How can we design the lightweight security schemes, such as encryption, to secure the current IC-IoT networks?

The aim of this Special Section in IEEE Access is to provide timely and comprehensive overviews of the current state-of-the-art in terms of fundamental theoretical innovations and technological advances and towards exploiting smart caching, communications, computing and cybersecurity for future IoT networks.

The topics of interest include, but are not limited to:

  • Advances in communication theory, technology, and architecture for IC-IoT
  • Smart mobile computing, edge computing, cloud computing for IC-IoT
  • Smart content push, distribution and caching for IC-IoT
  • Software-defined networking and network function virtualization solutions for IC-IoT
  • Smart and novel QoS and QoE provisionings of IC-IoT
  • Computing and analysis for big data in IC-IoT
  • Novel security situational awareness, threat intelligence analysis and security defense for IC-IoT
  • Lightweight cryptography algorithms for content privacy for IC-IoT
  • Experimental prototypes and test-bed for IC-IoT
  • Smart energy efficiency and energy harvesting in IC-IoT
  • Optimization solutions of caching, communication, computing and cybersecurity for IC-IoT
  • Emerging IC-IoT applications in novel networks such as Internet of Vehicle, 5G, space information network, smart city,
  • Standardization of caching, communications, computing and cybersecurity of IC-IoT
  • Novel artificial intelligence algorithms for smart caching, communications, computing and cybersecurity of IC-IoT

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Jun Wu, Shanghai Jiao Tong University, China

Guest Editors:

  1. Zhenyu Zhou, North China Electric Power University, China
  2. Mianxiong Dong, Muroran Institute of Technology, Japan
  3. Zheng Chang, University of Jyvaskyla, Finland
  4. Sandeep S. Kumar, Philips Lighting Research, The Netherlands
  5. William J. Miller, Maximum Control Technologies, USA

 

Relevant IEEE Access Special Sections:

  1. Security and Trusted Computing for Industrial Internet of Things
  2. Real-Time Edge Analytics for Big Data in Internet of Things
  3. Multimedia Analysis for Internet-of-Things

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: junwuhn@sjtu.edu.cn

Advanced Energy Storage Technologies and Their Applications

Submission Deadline: 31 May 2019

IEEE Access invites manuscript submissions in the area of Advanced energy storage technologies and their applications.

The depletion of fossil fuels, the increase of energy demands, and the concerns over climate change are the major driving forces for the development of renewable energy such as solar energy and wind power. However, the intermittency of renewable energy has hindered the deployment of large scale intermittent renewable energy, which, therefore, has necessitated the development of advanced large-scale energy storage technologies. The use of large scale energy storage can effectively improve the efficiency of energy resource utilization, and increase the use of variable renewable resources, the energy access and the end-use sector electrification (e.g. electrification of transport sector).

The main objective of this Special Section in IEEE Access is to provide a platform for presenting the latest research results on the technology development of large scale energy storage. We welcome research articles about theoretical, methodological and empirical studies, as well as review articles that provide a critical overview on the state-of-the-art of these technologies. This Special Section is open to all types of energy, such as thermal energy, mechanical energy, electrical energy and chemical energy, using different types of systems, such as phase change materials, batteries, supercapacitors, fuel cells, compressed air, etc., which are applicable to various types of applications, such as heat and power generation, electrical/hybrid transportation etc. Original, high quality technical articles as well as original review and survey articles are encouraged.

The topics of interest include, but are not limited to:

  • Novel energy storage materials and topologies
  • Application in electrical/hybrid driven system and electrical/hybrid vehicles
  • Next generation energy storage and conversion devices, systems or techniques
  • Large scale energy storage system modeling, simulation and optimization, including testing and modeling ageing processes
  • Advanced energy storage management systems, including advanced control algorithms and fault diagnosis/online condition monitoring for energy storage systems
  • Artificial Intelligence in Energy and Renewable Energy Systems
  • Wireless power transfer, charging systems and infrastructures
  • Big Data Analytics in Energy
  • Business model for the application and deployment of energy storage
  • Lifecycle analysis, repurposing, and recycling

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Rui Xiong, Beijing Institute of Technology, China

Guest Editors:

  1. Suleiman Sharkh, University of Southampton, UK
  2. Hailong Li, Mälardalen University, Sweden
  3. Kevin Bai, University of Michigan, USA
  4. Weixiang Shen, Swinburne University of Technology, Australia
  5. Peng Bai, Washington University in St. Louis, USA
  6. Joe Zhou, Kettering University, USA

 

Relevant IEEE Access Special Sections:

  1. Energy Management in Buildings
  2. Battery Energy Storage and Management Systems
  3. Advanced Modeling and Control of Complex Mechatronic Systems with Nonlinearity and Uncertainty

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: rxiong@bit.edu.cn

Molecular Communication Networks

Submission Deadline: 30 November 2018

IEEE Access invites manuscript submissions in the area of Molecular Communication Networks.

With an improved ability to manipulate matter at the nano and micro scales via synthetic biological and chemical techniques, there are now opportunities to address challenges ranging from disease diagnosis and treatment to environmental protection. A key framework to develop these tools is nano networking, where networks are built from nanoscale devices that are able to operate in nano to micrometer scale environments, and perform simple tasks such as sensing and actuation. However, the effectiveness of nano networking strongly depends on the ability for devices to coordinate.

Molecular communication has been proposed as a means of coordination in nano networks, where information is exchanged between devices via molecules emitted and absorbed by each device. The basic principles of molecular communication are based on mature aspects of physics, chemistry, biology as well as other areas including pharmacology, microfluidics and medicine. However, there remain a number of challenges in developing signal processing and communication techniques to encode and decode information, as well as develop practical implementations. A particular challenge is how to reliably embed molecular communication systems within existing biochemical systems, which is important for medical applications from the perspective of toxicity and undesirable side effects.

Authors are encouraged to submit articles presenting new research related to theory or practice of all aspects of molecular communications and networks. The topics of interest include, but are not limited to:

  • Theoretical Modeling (e.g., channel modeling, transmitter and receiver device modeling)
  • Architectures, Protocols, Optimal Design (e.g., modulation design, channel parameter estimation, detection, inter-symbol interference mitigation)
  • Transmitter/Receiver Mechanisms & Components
  • Multi-scale and experimental analysis of Molecular Communication Networks
  • Simulation Tools (e.g., tools, models, and approaches for developing simulation packages for Molecular Communication Networks)
  • Interoperability between Molecular Communication Networks and other systems (e.g., Internet of Nano Things, Internet of Bio-Nano Things, Intra-body communication, Body Area Nano-networks)
  • Implementation techniques and for Molecular Communication Networks (e.g., exploiting Nanotechnology and Nanobioscience)
  • Power Sources and Energy efficiency models for Molecular Communication Networks
  • Security in Molecular Communication Networks
  • Potential Applications for Molecular Communication Networks

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Daniel Benevides da Costa, Federal University of Ceará, Brazil

Guest Editors:

 

  1. Trung Q. Duong, Queen’s University, UK
  2. Chan-Byoung Chae, Yonsei University, South Korea
  3. Andrew Eckford, York University, Canada
  4. Malcolm Egan, INRIA and INSA Lyon, France
  5. Arumugam Nallanathan, Queen Mary University of London, UK
  6. Marco Di Renzo, Paris-Saclay University, France

 

Relevant IEEE Access Special Sections:

  1. Nano-antennas, Nano-transceivers, and Nano-networks / Communications
  2. Physical and Medium Access Control Layer Advances in 5G Wireless Networks
  3. Future Networks: Architectures, Protocols, and Applications

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: danielbcosta@ieee.org

Advances in Channel Coding for 5G and Beyond

Submission Deadline: 31 December 2018

IEEE Access invites manuscript submissions in the area of Advances in Channel Coding for 5G and Beyond.

In 1948, Shannon introduced the concept of channel capacity and proved the existence of error-correction codes (ECCs) that can realize reliable communication at any rate lower than the capacity. In the following 45 years, many researchers have endeavored to search for capacity-approaching ECCs, but obtained slow progress. Following the remarkable success of turbo codes in 1993, low-density parity-check (LDPC) codes were rediscovered. Since then, capacity-approaching ECCs have attracted more and more attention because it can significantly improve the performance of a myriad of communication systems, such as wireless communication systems, deep-space communication systems, optical communication systems, underwater acoustic communication systems, and data storage systems.

Compared with turbo codes, LDPC codes can achieve better performance and faster decoding. As such, LDPC codes have attracted growing interests in both academia and industry. Furthermore, many meritorious variants of LDPC codes, such as protograph LDPC codes and spatially coupled LDPC codes, were developed in the past decade.

In parallel with the advances in LDPC-based codes, some other capacity-approaching coding methodologies were conceived. In particular, as the first constructive codes achieving the capacity, Polar codes outperform LDPC codes in certain cases and represent an emerging class of ECCs for future wireless communications. Meanwhile, another powerful class of ECCs, called rateless codes (e.g., Luby transform (LT) codes and Raptor codes), was also extensively investigated. In practical applications, rateless codes are very suitable for scenarios where the channel state information (CSI) is unavailable at the transmitter terminal.

Recently, LDPC codes have been selected for the Enhanced Mobile Broadband (eMBB) data channels for 5G New Radio, while Polar codes have been chosen for the corresponding control channel. Beyond any doubt, LDPC codes, Polar codes, and their variants will find more deployment in many other applications and will be included in other new standards in the future. Nevertheless, the design of such codes for the next-generation wireless communication systems is still in its infancy. There are a range of open issues waiting to be addressed.

This Special Section in IEEE Access will focus on the theoretical and practical design issues of ECCs for 5G and beyond. Our aim is to bring together researchers, industry practitioners, and individuals working on the related areas to share their new ideas, latest findings, and state-of-the-art achievements with others. Both comprehensive surveys and original technical contributions are welcome.

The topics of interest include, but are not limited to:

  • LDPC codes
  • Polar codes
  • Rateless codes and their variants
  • Development trends and challenges for turbo codes
  • LDPC convolutional codes and spatially-coupled (SC) LDPC codes
  • Protograph codes and their variants
  • Algebraic constructions of low-density graph codes
  • Codes on factor graphs
  • Density evolution (DE) and extrinsic-information-transfer (EXIT) chart techniques
  • Minimum distance or weight distribution analysis for capacity-approaching codes
  • Finite-length analytical methodologies
  • Iterative decoding and turbo-like detection algorithms
  • Low-complexity LDPC/Polar codes and their hardware implementations
  • Channel coded modulations
  • Channel coding for non-orthogonal multiple access (NOMA)
  • Low-density graph codes for source coding
  • Low-density graph codes for compressed sensing (CS)
  • Joint source-and-channel coding (JSCC)
  • Joint channel-and-physical-layer-network coding (JCPNC)
  • Coded random access
  • Applications of ECCs to physical-layer security

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Yi Fang, Guangdong University of Technology, China

Guest Editors:

 

  1. Lars Kildehøj Rasmussen, Royal Institute of Technology, Sweden
  2. Yong Liang Guan, Nanyang Technological University, Singapore
  3. Kai Niu, Beijing University of Posts and Telecommunications, China
  4. Francis C. M. Lau, Hong Kong Polytechnic University, Hong Kong
  5. Soon Xin Ng, University of Southampton, UK
  6. Pingping Chen, Fuzhou University, China

 

Relevant IEEE Access Special Sections:

  1. Index Modulation Techniques for Next-Generation Wireless Networks
  2. Non-Orthogonal Multiple Access for 5G Systems
  3. Green Signal Processing for Wireless Communications and Networking


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: fangyi@gdut.edu.cn

Advanced Sensor Technologies on Water Monitoring and Modeling

Submission Deadline: 30 July 2019

IEEE Access invites manuscript submissions in the area of Advanced Sensor Technologies on Water Monitoring and Modeling.

Developing new methods and technologies for water pollution control, water resources management, and restoration of watershed ecosystems are critical for securing water security and sustainable development. The biophysicochemical parameters in an aqueous system, such as flow, hydraulic heads, temperature, pH, conductivity, turbidity, microorganisms, solutes concentration, etc., are of great significance in water research. Traditional methods for aqueous environmental monitoring and modeling are heavily dependent on instant point-in-space measurements, laboratory analysis, and physical and computing infrastructure. However, these methods are not only of high cost, but also are unable to timely provide many of the required spatiotemporal features. Thus, there is a clear need for continuous on-line monitoring water quality and hydrologic conditions using advanced sensors technologies across spatiotemporal resolutions.

The rapid expansion of Internet of Things (IoT) technologies, cloud computing and big data promote unprecedented advances in signal processing and information system. Such advances support the development of sensing technologies, as well as software-defined networks, which allow effective monitoring and modeling for water issues. Sensing and control systems that are suitable for the effective monitoring of biophysicochemical parameters, as well as for detecting concentrations of interest in solutes, are crucial to investigate water health and chemical evolutions, and also to timely implement prevention and management strategies.

The purpose of this Special Section in IEEE Access is to solicit manuscripts on the emerging trends, issues, and challenges in smart sensing for aqueous environment monitoring and modeling. Practical studies describing techniques or information system for real-time and in-situ recording of biophysicochemical parameters in an aqueous environment are encouraged. Letters, reports, and reviews with a multidisciplinary focus are also welcome. Topics of interest include, but are not limited to:

  • Advanced sensing technologies in aqueous environments
  • Low cost, portable optical sensing technologies for water monitoring
  • Design, simulation and implementation of sensor systems for water leakage monitoring
  • Water quality sensing in Water Distribution System (WDS)
  • Wireless Sensor Networks (WSNs) for water resource management and control
  • Web-based system analysis and modeling in urban water systems
  • Smartphone-based mobile water monitoring and heterogeneous sensor network
  • Transportation and environmental pollution analysis on water quality
  • Real-time flood forecasting and warning systems
  • Novel monitoring system for municipal water pipes
  • Remote Hydrologic Sensor Networks in the context of citizen science
  • Underwater acoustic signaling and interactive visualizing technologies
  • Real-time, on-site and in-situ monitoring in water and marine environments
  • Robotic and autonomous hydraulic information monitoring infrastructures
  • Experimental network measurements and characterization for aqueous monitoring
  • Water data processing pipelines and data product generation
  • Water data life-cycle management and end-to-end systems
  • Data quality assurance and quality control for observational water data
  • Innovation in water and healthy environments research
  • Adaptive measurements collection, acquisition, management, and visualization
  • Sustainable water management and cost-benefit analysis
  • Security issues and solutions for privacy in an aqueous environment

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Xiang Huang, Zhongnan University of Economics and Law, China

Guest Editors:

  1. Jie Liu, Peking University, China
  2. Eftichios Koutroulis, Technical University of Crete, Greece
  3. Branko Kerkez, University of Michigan, USA
  4. Gilberto Pastorello, Lawrence Berkeley National Laboratory, USA
  5. Nick R. Harris, University of Southampton, UK.

 

Relevant IEEE Access Special Sections:

  1. Underwater Wireless Communications and Networking
  2. Multiphase Flow Measurement: Techniques and Applications
  3. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: huangx07@gmail.com

Trends, Perspectives and Prospects of Machine Learning Applied to Biomedical Systems in Internet of Medical Things

Submission Deadline: 31 October 2018

IEEE Access invites manuscript submissions in the area of Trends, Perspectives and Prospects of Machine Learning Applied to Biomedical Systems in Internet of Medical Things.

The recent advancement in Internet of Medical Things (IoMT) paradigm aims to enrich our perception of healthcare reality, and incorporating new technologies for such applications. In the context of the IoMT, several medical devices connected to healthcare IT infrastructure can offer superior and more personalized health services. The combination of IoMT data, machine learning, streaming analytics distributed computing, and biomedical systems has become more powerful by enabling the storage and analysis of more data and many different types of data much faster. Machine learning plays a crucial role in the medical imaging field, comprising computer-aided diagnosis, registration and fusion, image segmentation, image-guided therapy, and image database retrieval for providing a better understanding of medical data applied to biomedical systems in IoMT. Moreover, the potential of big data in IoMT is a critical concern to constructing and running the kinds of big data analytics applications are obligatory for IoMT data. Thus it necessitates key focus from academia and industries.

Medical data is central to the IoMT paradigm: from acquiring critical medical sensor data or imaging data to analyzing, processing, and storing of health information, which adds new insights to our view of the world. Machine learning is essential to challenges related to the data source applied to biomedical devices using IoMT. Machine learning and data-driven methods represent a paradigm shift, and they are bound to have a transformative impact in the area of medical data and imaging processing. Many challenges arise as the IoMT permeates our world, especially for low-power resource-constrained devices for accumulating patient’s data, medical data integrity, privacy and security, and network lifetime and quality of service among others. The primary goal of this Special Section in IEEE Access is to provide an overview of the current state-of-the-art advances in machine learning of data source for understanding IoMT.

Topics of interest include, but are not limited to:

  • Computer-aided detection or diagnosis applied to biomedical systems in IoMT
  • New imaging modalities or methodologies for IoMT
  • Innovative machine-learning algorithms or applications in IoMT
  • Medical data security and privacy techniques for healthcare
  • Energy harvesting and big data analytics strategies in IoMT
  • Deep learning for optimizing medical big data in IoMT
  • Low-power resource-constrained medical devices for IoMT
  • Associative rule learning and reinforcement learning in IoMT
  • Smart medical systems based on cloud-assisted body area networks
  • Flexible and wearable sensors for prognosis and follow-up based on IoMT Paradigm
  • Healthcare Informatics to analyze patient health records, for enabling better clinical decision making and improved healthcare outcomes

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Kelvin KL Wong, Western Sydney University, Australia

Guest Editors:

  1. Dhanjoo N Ghista, University 2020 Foundation, USA
  2. Giancarlo Fortino, University of Calabria (Unical), Italy
  3. Wanqing Wu, Chinese Academy of Sciences, China

 

Relevant IEEE Access Special Sections:

  1. Mobile Multimedia for Healthcare
  2. Health Informatics for the Developing World
  3. Soft Computing Techniques for Image Analysis in the Medical Industry – Current trends, Challenges and Solutions

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: Kelvin.Wong@westernsydney.edu.au