Journal Information
IEEE Communications Magazine
http://www.comsoc.org/commag
Impact Factor:
5.125
Publisher:
IEEE
ISSN:
0163-6804
Viewed:
5854
Tracked:
12

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Call For Papers
IEEE Communications Magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications systems (PCS), ISDN, and more. It includes special feature technical articles and monthly departments: book reviews, conferences, short courses, standards, governmental regulations and legislation, new products, and Society news such as administration and elections.
Last updated by Dou Sun in 2017-03-30
Special Issues
Special Issue on Amateur Drone Surveillance: Applications, Architectures, Enabling Technologies, and Public Safety
Submission Date: 2017-05-01

The advancement in communication, networking, computation, and sensing technologies has attracted researchers, hobbyists, and investors to deploy mini-drones, officially called unmanned aerial vehicles (UAVs), due to their enormous applications. Drones have boundless viable applications as well due to their small size and capability to fly without an on-board pilot such as in agriculture, photography, surveillance, and numerous public services. The use of drones for achieving high-speed wireless communication is one of the most significant applications for next-generation communication systems (5G). Indeed, drone-based communication network offers versatile solutions to provide wireless connectivity for devices without infrastructure coverage due to e.g., severe shadowing by urban or mountainous terrain, or damage to the communications infrastructure caused by natural disasters. But its deployment poses several public safety (PS) threats to national institutions and assets such as nuclear power plants, historical sites, and government leaders' houses because of drone's ability to carry the explosive and other destructive chemicals and agents. In order to cope with these security threats, surveillance drones (SDrs) deployment is required for surveillance, hunting, and jamming of the amateur drone (ADr). The main motivation of deploying SDrs is to keep an eye on the ADr which can lead to serious disasters in cases where no precautionary measures are taken in a timely manner. The SDr architecture should have the capability to self-configure in case of emergency situations without the help of the central ground control station (GCS). The increasing usage of SDr in surveillance of ADr presents some challenges such as robust detection, tracking, intruder localization, and jamming. The accuracy of detection is a basic requirement of the system. In general, the accurate detection is time-consuming. In fact, a precise moving object detection method makes tracking more reliable and faster, and supports correct classification, which is quite important for SDr to be successful. The existing motion detection algorithms have the problems of computational cost and lower robustness. However, because of rapidly changing extrinsic and intrinsic camera parameters such as pan, tilt, translation, rotation, and zooming, algorithms of highest accuracy are required. Moreover, the machine learning and pattern recognition algorithms are required to detect the ADr by using the characteristics of the electromagnetic waves, sound, images that can efficiently detect the ADr. The next major step after detecting the ADr is its tracking and the localization of the ADr intruder. To accurately estimate the position of the ADr and its intruder, the 3D position estimation algorithms are desired to accurately determine the position of the ADr. The FANET (Flying Ad Hoc Networks) architecture-based deployment and utilization of the commercial frequency bands for SDr also presents the challenges of interference management with the existing system. So, proper spectrum management schemes are desired which can take care of the dynamically changing environment while allocating the spectrum. The last important step after detection, localization, and tracking is the Jamming and hunting of the ADr. For example, the jamming technologies such as by using excess power and global positioning services (GPS) spoofing can generate the high interference to the SDr signal. So, Jamming signal power control algorithm needs to be designed to avoid surrounding SDr jamming. After jamming the ADr, hunting of the ADr should be done by taking care of security of the surrounding environment. That is, ADr in the air should be landed outside the highly sensitive areas. Thus, to get this goal context-aware path-design algorithms are required to safely land the hunted ADr. Hence, the technologies like frequency band recognition, power control, jamming and hunting are required to efficiently detect, control, jam, and hunt the ADr. The goal of the proposed Feature Topic (FT) is to publish comprehensive original research for all readers of the Magazine regardless of their specialty. The main objective of this FT is to bring most recent advances in amateur drone surveillance network architecture and technologies. Moreover, its goal is to address the challenges related to public safety issues posed by the flying of drone in the No-fly zone.
Last updated by Dou Sun in 2017-02-12
Special Issue on Education & Training: Scholarship of Teaching and Supervision
Submission Date: 2017-05-01

The Scholarship of Teaching and Learning (SoTL) encourages educators to examine their own classroom practice, record their successes and failures, and ultimately share their experiences in a formal and scholarly way so that others may reflect on their findings and build upon teaching and learning processes. SoTL acknowledges that concerns for privacy and other ethical issues associated with studies involving human subjects place limits on the types of research that can be conducted in classroom setting. Nevertheless, SoTL provides a mechanism for raising the standard of discussion concerning teaching and learning in the literature. The Scholarship of Research and Supervision (SoRL) is a related concept that invites the same reflective approach to improving the quality of training through research, especially that conducted at the postgraduate level. SoRL invites researchers to examine their own supervisory practice, record their successes and failures, and ultimately share their experiences in a formal and scholarly way so that others may reflect on their findings and improve research and supervision processes. This feature topic on the Scholarship of Teaching and Supervision is intended to hasten the incorporation of SoTL and SoRL into communications engineering curricula by providing educators and researchers with an opportunity to share their experience, best practices and case studies.
Last updated by Dou Sun in 2016-10-17
Special Issue on Heterogeneous Ultra Dense Networks
Submission Date: 2017-05-15

Driven by the development of mobile Internet and smart phones, data traffic grows exponentially in current mobile networks. Initial estimations indicate that, differently from the evolutionary path of previous cellular generations that were based on spectral efficiency improvements, the most substantial amount of future system performance gains will be obtained by means of network infrastructure densification. The opportunities and challenges of the fifth-generation (5G) technologies rapidly gain great attention from academics, industries, and governments. Ultra dense network (UDN) is a promising technique to meet the requirements of explosive data traffic in 5G mobile communications. Moreover, when overlaid on top of the macrocells, low power small cells (such as femtocell and picocell) can improve the coverage and capacity of cellular networks by exploiting spatial reuse of limited spectrum. Dense small cells can also offload the wireless data traffic of user equipment (UE) from macrocells, especially for an indoor environment where more than 80% of data traffic takes place.
Last updated by Dou Sun in 2017-02-12
Special Issue on Imminent Communication Technologies for Smart Communities
Submission Date: 2017-06-01

Most of the research and technological advancements have vitalized the ubiquitous information access and communication around the globe. The connectivity has been extended from unmanned aerial vehicles, self- driving vehicles on the road, power generation plus distribution hubs, industries, markets, to the tiny wireless communication devices that are expected to be attached with everything situated onshore, offshore, or in the air. All of these devices generate and share information to be accessed by communities (ranging from a block to a nation), which will improve their quality of life by making smart decisions. Access to such information (real-time to big data) should be open to all members and classes of any Smart Community. Hence, the technology, more specifically, the communication technology, plays an important role to realize a smarter community. Having said that, the existing Internet architecture is host centric and intended for end-to-end communication between hosts by establishing a path first. This architecture has evolved to enable communication between varying-nature protocols, Bluetooth, ZigBee, LTE, etc. that increased the network complexity. As a result, the academia and industrial collaboration are making attempts to substrate the connectivity, routing, and other functions and transfer all the functions to software rather than embedding it within the hardware. This continual transformation in communication technologies keep improving the QoS and QoE despite their roots in mobile networks, content delivery, home connectivity, wireless, enterprise, IoT, data centers, cloud computing, and backbone networks. Likewise, the IoT is progressively being used by various firms and industries for the planning and development of future Smart Communities. However, without utilizing the previous context of the cities, it is quite difficult to design and build a foreseen future Smart Community. Therefore, the data generated by various IoT-enabled devices needs to be efficiently processed through various techniques and tools such as Hadoop ecosystem, etc. However, the existing techniques based on Map-Reduce paradigm, etc. are mainly designed to process offline data. Moreover, the existing technologies such as Software Defined Network (SDN), etc. can be made more intelligent and efficient to communicate the huge amount of data over the existing network with high speed. The theme of this Feature Topic is to provide an in-depth analysis both theoretically and analytically of the current advances in processing real-time data for optimal planning and management of a smart community. Moreover, we are looking for answers of the following questions: How much is the effect of SDN can be in simplifying the enormous devices setup in developing Smart Communities? On the contrary, where do we need to focus on while bridging current networking technologies to build smarter communities? What kind of education and training are required for citizens of such communities to take full benefits of the proposed architectures? What kind of ground breaking applications can make communities smarter? What will be the acceptability aspects of Smart Communities? In addition, the authors are expected to investigate state-of-art research challenges, results, architecture, applications, and other achievements. Topics of interest include, but are not limited to: Smart Community architectures and planning using WSN The role of IoT in the planning of future Smart Communities Smart management and services Deployment of sensors and embedded devices Smart homes, Buildings, Campuses, and Applications The role of Cloud Computing in IoT-based Smart Communities Big Data Analytics and Smart Communities IoT-enabled devices and technologies Real-Time data processing using Hadoop, SPARK, GraphLab, etc. System, design, modeling and evaluation Industrial applications of Smart Communities Future Internet cohesion with applications for Smart Communities
Last updated by Dou Sun in 2017-03-30
Special Issue on Mobile Big Data for Urban Analytics
Submission Date: 2017-06-01

The rapid progress of urbanization, especially in developing countries, has led to many big cities, which have modernized people’s lives but also engendered big challenges such as air pollution, traffic congestion and increased energy consumption. To deal with these challenges, more effective and efficient information systems need to be developed, including communication, networking and computation infrastructures. Nowadays, sensing technologies and telecommunication infrastructures paired with powerful large-scale computing infrastructure enable the collection and processing of large quantities of diverse mobile data about urban spaces and its population, e.g., human mobility, air quality, traffic patterns, and geographical data. These mobile big data sources provide information and knowledge about a city and can help improve quality of life and functioning of cities when used appropriately. Mobile Big Data for Urban Analytics is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces such as sensors, devices, vehicles, buildings, and human inhabitants to address the urban issues faced by city information infrastructures. One important aspect for this FT (Feature Topic) is the understanding of human behavior in urban environments and the corresponding requirements in terms of human communications and their interplay and mutual influence with mobile networks and services. This FT is calling for papers that deal with the technical problems mentioned above. Topics for the FT include, but are not limited to: City-wide data collection: practice and theory; City-wide mobile traffic modeling, visualization, analysis, and prediction; City-wide human mobility modeling, visualization, and understanding; Human behavior modeling and mining in urban environment; Social behavior modeling, understanding, and patterns mining in urban spaces; Application of urban computing to the design of distributed and mobile urban systems; Data mining of large scale urban networks and big data; Urban computing applied to forwarding/routing problems of mobile networks; Application of social network analysis to urban communication and computing system design; Urban computing for urban networks and computation system; City-wide intelligent transportation systems including vehicular networks; City-wide mobile social applications in urban areas; Location-based social networks enabling urban computing scenarios.
Last updated by Dou Sun in 2017-03-30
Special Issue on Point-to-Multipoint Communications and Broadcasting in 5G
Submission Date: 2017-06-30

In the last few years since the development of the Internet, streaming video and mobile devices such as Tablets and Smartphone have played prominent roles in modern daily life, and the global communications industry has started working on new, more effective digital broadcast systems that can simultaneously deliver signals to both fixed and mobile devices. Digital broadcast systems are suitable for large-volume broadband information delivery, especially for multimedia communication. In fact, the global rapid growth of mobile data traffic is primarily driven by the massive deployment of mobile video services on modern large-screen devices. In the 3rd Generation Partnership Project (3GPP) Release 9 standards, multimedia broadcast/multicast service (MBMS) has evolved to achieve improved performance with higher speed and more flexible service configuration, named as evolved MBMS (eMBMS). 3GPP Release 11 has also improved service layer with video codec for higher resolution and frame rate and introduced Forward Error Correction (FEC) technique. New technologies such as time frequency slicing (TFS) can increase the network spectral efficiency (in terms of bps/Hz) by potentially tolerating a higher carrier-to-interference signal (C/I) ratio for the network. The TFS is part of an informative (not normative) annex of the digital video broadcasting terrestrial 2nd generation (DVB-T2) specification and is fully adopted in the mobile broadcasting standard digital video broadcasting next generation handheld (DVB-NGH) specification. It is also proposed to adopt layered division multiplexing (LDM) in the upcoming advanced television system committee (ATSC) 3.0 standards, where multiple physical layer data streams are superimposed with different power levels, channel coding and modulation schemes for different services and reception environments. However, in 5G, traffic data volume and terminal mobility model will change dramatically compared with the existing 4G and other communications systems. Related studies and implementation of new technologies are constantly challenged with the growth of requirements by large numbers of users, improved device capabilities and deployment of higher capacity networks. To create new hybrid services and augmented regular broadcasts with greater interactivity, current development projects address the following requirements that may apply in 5G: 1) Higher quality signals and better source coding, such as immersive audio, Ultra HDTV, and multi-screen/multi-view system, 2) Simultaneously broadcast everywhere, to both fixed users at home and mobile users on smart phones and tablets. 3) Higher data volume and density of transmission, such as super layered division multiplexing (SLDM). 4) Terminal mobility considering fast moving scenarios. To meet these requirements, proposed solutions include the following items: 1) More effective utilization of spectrum. 2) Providing broadcasters the option to offer multiple channels within the same bandwidth, plus the ability to simultaneously broadcast to TVs at home and to Smartphones / Tablets on the go. 3) Cooperation among cells to support broadcasting demands, 4) Broadcast transmission of content developed for and sent over the Internet based on the Internet protocol. To seek solutions to the current challenges, we have planned this Feature Topic (FT) to describe recent progress in academic and industrial research and help both the industrial and academic research communities better understand the progress and potential research areas on the converging paths of point to multi-point communications and broadcasting in 5G.
Last updated by Dou Sun in 2017-02-12
Special Issue on Advances in Next-Generation Networking Technologies for Smart Healthcare
Submission Date: 2017-08-01

With the advancement of next-generation mobile and wireless networking technologies, “Smart healthcare” and/or “Connected Healthcare“ is getting tremendous attention from the academia, the governments, the industry, and the healthcare community. The next generation mobile and wireless networking technologies such as 5G wireless networks, mobile-edge computing (MEC), software-defined networking (SDN), and cloud radio access networks (Cloud RAN), can play a significant role in the smart healthcare by offering better insight of heterogeneous healthcare media content to support affordable and quality patient care. While researchers have been making advances to the study of next-generation networking and healthcare services individually, a very little attention has been given to make cost-effective and affordable smart healthcare solutions. Connected or smart healthcare has the potential to revolutionize many aspects of our society; however, many technical challenges need to be addressed before this potential can be realized. Some of these challenges include how to develop rich and real-time services or applications for smart healthcare solutions by adopting next generation mobile and wireless networking technologies? How can the next-generation networking technologies assist with right patient care at the right time and in the right place? How can networking technologies facilitate healthcare data representation, storage, analysis and integration for effective smart healthcare solutions? The next-generation wireless technology that makes highly connected healthcare environments has the potential to address each of those challenges and can revolutionize the future of connected healthcare services. It is envisioned that the next-generation networking technologies will be the success factor for realizing the true vision of smart healthcare since they will contribute to facilitate resource constrained devices to communicate efficiently, faster data generation and processing as well as for quality data transmission to stakeholders. This Feature Topic is intended to report high-quality research on recent advances in various aspects of the next-generation networking technologies in healthcare services, more specifically to the state-of-the-art approaches, methodologies, and systems in the design, development, deployment and innovative use of those networking technologies for providing insights into smart healthcare service demands. Authors are solicited to submit complete unpublished papers on the following topics. Topic includes but not restricted to: Cloud RAN for smart healthcare Software-defined wireless networks for smart healthcare Mobile Edge Computing for smart healthcare IoT-Cloud for smart healthcare Wireless technologies for connected medicine Cyber-physical and socially-aware network for smart healthcare Context-aware 5G-supported services for smart healthcare Data security, and privacy for connected healthcare Wearable Internet of Things (WIoT) and 5G access technologies for smart healthcare Innovative communication protocols, algorithms and test beds for 5G-enable connected healthcare
Last updated by Dou Sun in 2017-03-30
Special Issue on Key Technologies for 5G New Radio
Submission Date: 2017-08-01

With expected 2020 initial commercialization, 5G mobile communications is gathering increased interest and momentum around the world. Following discussions on the 5G vision and key requirements (such as high data-rate, low latency, and massive connectivity), various candidate technologies have been proposed and investigated. The candidate enablers for 5G mobile communications include massive antenna technologies (from legacy cellular frequency bands up to high frequencies) to provide beamforming gain and support increased capacity, new waveform (or a new radio access technology (RAT)) to flexibly accommodate various services/applications with different requirements, new multiple access schemes to support massive connections, and so on. The International Telecommunication Union (ITU) has categorized the usage scenarios for International Mobile Telecommunications (IMT) for 2020 and beyond into three main groups: Enhanced Mobile Broadband, Massive Machine-Type Communications, and Ultra-reliable and Low Latency communications. In addition, they have specified target requirements such as peak data rates of 20 Gb/s, user experienced data rates of 100 Mb/s, a spectrum efficiency improvement of 3X, support for up to 500 km/h mobility, 1 ms latency, a connection density of 106 devices/km2, a network energy efficiency improvement of 100X and an area traffic capacity of 10 Mb/s/m2. While all the requirements need not be met simultaneously, the design of 5G networks and radio access should provide flexibility to more efficiently support various applications meeting part of the above requirements on a use case basis. There is also increased interest in the use of spectrum above 6 GHz for 5G mobile communications. Several researchers in academia and industry have explored the feasibility of using mmWave frequencies for 5G mobile communications, considering frequencies up to 100 GHz. This has also been supported by regulatory bodies with ITU-R investigating the spectrum between 6 – 100 GHz for possible global harmonization and usage by 2020 and regulatory bodies such as FCC in the US and OFCOM in UK, starting a notice-of-inquiry (NOI) for using mmWave spectrum for mobile communications. 3GPP has officially started the standardization of 5G and the new 5G spec is codenamed NR (New Radio) in 3GPP discussions. The study on 5G use cases, requirements and key technology components are expected to be completed by March 2017, with the first official release of core radio spec slated for the first half of 2018. We think it is a very timely Feature Topic if we can bring a first look of the key technologies of 5G New Radio to the IEEE Communication Magazine readers in early 2018. With this Feature Topic, our hope is that researchers worldwide can understand the state-of-art of these 5G technologies, both in terms of their design considerations and, equally importantly, their limitations, so that they can use these references to guide their research for future releases of 5G. Scope Original contributions are invited on the latest advancements on key component technologies of 5G New Radio, especially in the following areas of 5G NR system design: NR-MIMO, especially new feedback and reference signal methods NR control mechanism for reducing signaling overhead and improving battery life Support of new 5G bands, including both mmWave bands and below 6GHz bands Beam-centric or UE centric cellular design in support of seamless mobility and UE experience enhancement New channel coding in NR: LDPC and Polar codes Technologies for low latency transmission
Last updated by Dou Sun in 2017-03-30
Special Issue on Multi-Channel Cognitive Radio Ad Hoc Networks
Submission Date: 2017-08-01

Cognitive radio (CR) is an emerging network technology that has been around for more than 15 years towards solving the problem of wireless network spectrum inefficiency. Cognitive radio ad hoc networks (CRAHNs), equipped with the intrinsic capabilities of cognition and self-organization, provides an ultimate spectrum-aware communication paradigm in wireless networks. By nature, CRAHNs mostly operate on multiple channels based on the fact that the available spectrum usually appears as discontinuous spectrum. Concurrent communication over multi-channel CRAHNs can alleviate interference and improve the spectrum utilization with greater flexibility for channel access. However, multi-channel CRAHNs impose unique challenges as a result of high fluctuation in the available spectrum, distributed dynamic network topology, and the time and location varying spectrum availability. To overcome these challenges, some fundamental problems in multi-channel CRAHNs have to be carefully resolved, both in theory and in practice. Specifically, the following key questions need to be addressed: How can the fragmented available spectrum be recognized? How can multiple channels with the available spectrum be constructed in an efficient way? How can the multiple channels be allocated among the users and coordinate their concurrent communications in a distributed manner? How to evaluate the abilities of CRAHNs to support the quality of end-to-end services? This Feature Topic (FT) solicits technical papers describing original, previously unpublished, not currently under review by another conference or journal pertaining to trends and issues and challenges of multi-channel CRAHNs. The scope of this Feature Topic calls for novel research contributions including, but not restricted to the following topics. New theories, architectures and models for multi-channel CRAHNs Capacity analysis for multi-channel CRAHNs Spectrum sensing, sharing and management in CRAHNs Medium access control, scheduling, and routing protocols for multi-channel cognitive radio networks Transport layer design, TCP extension for multi-channel cognitive radio networks Joint route and spectrum allocation, adaptive cross-layer design and optimized resource management Security challenges in multi-channel CRAHNs Application scenarios and emerging markets over multi-channel CRAHNs, such as smart grids, emergency responders, disaster recovery, high bandwidth multimedia communication, military deployment, and homeland security among others.
Last updated by Dou Sun in 2017-03-30
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