Showing papers in "IEEE Wireless Communications in 2017"
TL;DR: The goal is to assist the readers in refining the motivation, problem formulation, and methodology of powerful machine learning algorithms in the context of future networks in order to tap into hitherto unexplored applications and services.
Abstract: Next-generation wireless networks are expected to support extremely high data rates and radically new applications, which require a new wireless radio technology paradigm. The challenge is that of assisting the radio in intelligent adaptive learning and decision making, so that the diverse requirements of next-generation wireless networks can be satisfied. Machine learning is one of the most promising artificial intelligence tools, conceived to support smart radio terminals. Future smart 5G mobile terminals are expected to autonomously access the most meritorious spectral bands with the aid of sophisticated spectral efficiency learning and inference, in order to control the transmission power, while relying on energy efficiency learning/inference and simultaneously adjusting the transmission protocols with the aid of quality of service learning/inference. Hence we briefly review the rudimentary concepts of machine learning and propose their employment in the compelling applications of 5G networks, including cognitive radios, massive MIMOs, femto/small cells, heterogeneous networks, smart grid, energy harvesting, device-todevice communications, and so on. Our goal is to assist the readers in refining the motivation, problem formulation, and methodology of powerful machine learning algorithms in the context of future networks in order to tap into hitherto unexplored applications and services.
958 citations
TL;DR: In this article, the authors provide an overview of the latest research on both green 5G techniques and energy harvesting for communication, and some technical challenges and potential research topics for realizing sustainable green wireless networks are also identified.
Abstract: The stringent requirements of a 1000x increase in data traffic and 1 ms round-trip latency have made limiting the potentially tremendous ensuing energy consumption one of the most challenging problems for the design of the upcoming 5G networks. To enable sustainable 5G networks, new technologies have been proposed to improve the system energy efficiency, and alternative energy sources are introduced to reduce our dependence on traditional fossil fuels. In particular, various 5G techniques target the reduction of the energy consumption without sacrificing the quality of service. Meanwhile, energy harvesting technologies, which enable communication transceivers to harvest energy from various renewable resources and ambient radio frequency signals for communication, have drawn significant interest from both academia and industry. In this article, we provide an overview of the latest research on both green 5G techniques and energy harvesting for communication. In addition, some technical challenges and potential research topics for realizing sustainable green 5G networks are also identified.
535 citations
TL;DR: This article investigates, highlight, and report premier research advances made in IoT architecture recently, categorize and classify IoT architectures and devise a taxonomy based on important parameters such as applications, enabling technologies, business objectives, architectural requirements, network topologies, and IoT platform architecture types.
Abstract: Recent years have witnessed tremendous growth in the number of smart devices, wireless technologies, and sensors. In the foreseeable future, it is expected that trillions of devices will be connected to the Internet. Thus, to accommodate such a voluminous number of devices, scalable, flexible, interoperable, energy-efficient, and secure network architectures are required. This article aims to explore IoT architectures. In this context, first, we investigate, highlight, and report premier research advances made in IoT architecture recently. Then we categorize and classify IoT architectures and devise a taxonomy based on important parameters such as applications, enabling technologies, business objectives, architectural requirements, network topologies, and IoT platform architecture types. We identify and outline the key requirements for future IoT architecture. A few prominent case studies on IoT are discovered and presented. Finally, we enumerate and outline future research challenges.
492 citations
TL;DR: The opportunities and challenges to exploit AI to achieve intelligent 5G networks, and the effectiveness of AI to manage and orchestrate cellular network resources are highlighted, and it is envisioned that AI-empowered 5G cellular networks will make the acclaimed ICT enabler a reality.
Abstract: 5G cellular networks are assumed to be the key enabler and infrastructure provider in the ICT industry, by offering a variety of services with diverse requirements. The standardization of 5G cellular networks is being expedited, which also implies more of the candidate technologies will be adopted. Therefore, it is worthwhile to provide insight into the candidate techniques as a whole and examine the design philosophy behind them. In this article, we try to highlight one of the most fundamental features among the revolutionary techniques in the 5G era, i.e., there emerges initial intelligence in nearly every important aspect of cellular networks, including radio resource management, mobility management, service provisioning management, and so on. However, faced with ever-increasingly complicated configuration issues and blossoming new service requirements, it is still insufficient for 5G cellular networks if it lacks complete AI functionalities. Hence, we further introduce fundamental concepts in AI and discuss the relationship between AI and the candidate techniques in 5G cellular networks. Specifically, we highlight the opportunities and challenges to exploit AI to achieve intelligent 5G networks, and demonstrate the effectiveness of AI to manage and orchestrate cellular network resources. We envision that AI-empowered 5G cellular networks will make the acclaimed ICT enabler a reality.
473 citations
TL;DR: An overview of CR-based IoT systems, including architectures and frameworks, is presented and potential applications and open issues, research challenges, and future direction for these CR- based IoT networks are presented.
Abstract: Recent research and technology trends are shifting toward IoT and CRNs. However, we think that the things-oriented, Internet-oriented, and semantic-oriented versions of IoT are meaningless if IoT objects are not equipped with cognitive radio capability. Equipping IoT objects with CR capability has lead to a new research dimension of CR-based IoT. In this article, we present an overview of CR-based IoT systems. We highlight potential applications of CR-based IoT systems. We survey architectures and frameworks of CR-based IoT systems. We furthermore discuss spectrum-related functionalities for CR-based IoT systems. Finally, we present open issues, research challenges, and future direction for these CR-based IoT networks.
380 citations
TL;DR: The potential of 4.5G and 5G networks to serve both the high data rate needs of conventional human-type communication subscribers and the forecasted billions of new MTC devices is focused on.
Abstract: Cellular networks have been engineered and optimized to carrying ever-increasing amounts of mobile data, but over the last few years, a new class of applications based on machine-centric communications has begun to emerge. Automated devices such as sensors, tracking devices, and meters, often referred to as machine-to-machine (M2M) or machine-type communications (MTC), introduce an attractive revenue stream for mobile network operators, if a massive number of them can be efficiently supported. The novel technical challenges posed by MTC applications include increased overhead and control signaling as well as diverse application-specific constraints such as ultra-low complexity, extreme energy efficiency, critical timing, and continuous data intensive uploading. This article explains the new requirements and challenges that large-scale MTC applications introduce, and provides a survey of key techniques for overcoming them. We focus on the potential of 4.5G and 5G networks to serve both the high data rate needs of conventional human-type communication (HTC) subscribers and the forecasted billions of new MTC devices. We also opine on attractive economic models that will enable this new class of cellular subscribers to grow to its full potential.
376 citations
TL;DR: The specific signal characteristics of 5G communication turn out to be highly conducive for vehicle positioning and can work in synergy with existing on-vehicle positioning and mapping systems to provide redundancy for certain applications, in particular automated driving.
Abstract: 5G technologies present a new paradigm to provide connectivity to vehicles, in support of high data-rate services, complementing existing inter-vehicle communication standards based on IEEE 802.11p. As we argue, the specific signal characteristics of 5G communication turn out to be highly conducive for vehicle positioning. Hence, 5G can work in synergy with existing on-vehicle positioning and mapping systems to provide redundancy for certain applications, in particular automated driving. This article provides an overview of the evolution of cellular positioning and discusses the key properties of 5G as they relate to vehicular positioning. Open research challenges are presented.
371 citations
TL;DR: Preliminary results are reported that demonstrate the encouraging performance of the proposed deep learning system compared to a benchmark routing strategy (Open Shortest Path First (OSPF)) in terms of significantly better signaling overhead, throughput, and delay.
Abstract: Recently, deep learning, an emerging machine learning technique, is garnering a lot of research attention in several computer science areas. However, to the best of our knowledge, its application to improve heterogeneous network traffic control (which is an important and challenging area by its own merit) has yet to appear because of the difficult challenge in characterizing the appropriate input and output patterns for a deep learning system to correctly reflect the highly dynamic nature of large-scale heterogeneous networks. In this vein, in this article, we propose appropriate input and output characterizations of heterogeneous network traffic and propose a supervised deep neural network system. We describe how our proposed system works and how it differs from traditional neural networks. Also, preliminary results are reported that demonstrate the encouraging performance of our proposed deep learning system compared to a benchmark routing strategy (Open Shortest Path First (OSPF)) in terms of significantly better signaling overhead, throughput, and delay.
342 citations
TL;DR: In this article, the issues involved in the design of antenna array architecture for future 5G mmw systems, in which the antenna elements can be deployed in the shapes of a cross, circle, or hexagon, are discussed, in addition to the conventional rectangle.
Abstract: As there has been an explosive increase in wireless data traffic, mmw communication has become one of the most attractive techniques in the 5G mobile communications systems. Although mmw communication systems have been successfully applied to indoor scenarios, various external factors in an outdoor environment limit the applications of mobile communication systems working at the mmw bands. In this article, we discuss the issues involved in the design of antenna array architecture for future 5G mmw systems, in which the antenna elements can be deployed in the shapes of a cross, circle, or hexagon, in addition to the conventional rectangle. The simulation results indicate that while there always exists a non-trivial gain fluctuation in other regular antenna arrays, the circular antenna array has a flat gain in the main lobe of the radiation pattern with varying angles. This makes the circular antenna array more robust to angle variations that frequently occur due to antenna vibration in an outdoor environment. In addition, in order to guarantee effective coverage of mmw communication systems, possible solutions such as distributed antenna systems and cooperative multi-hop relaying are discussed, together with the design of mmw antenna arrays. Furthermore, other challenges for the implementation of mmw cellular networks, for example, blockage, communication security, hardware development, and so on, are discussed, as are potential solutions.
271 citations
TL;DR: A survey of the recent development of advanced techniques for spectrum sharing, in particular, cognitive radio, device-todevice communication, in-band full-duplex communication, non-orthogonal multiple access, and Long Term Evolution on unlicensed spectrum is provided.
Abstract: Spectrum efficiency is one of the key performance metrics in 5G communication networks. To enhance spectrum efficiency, advanced spectrum sharing techniques are normally used. In this article, we provide a survey of the recent development of advanced techniques for spectrum sharing. In particular, we elaborate cognitive radio, device-todevice communication, in-band full-duplex communication, non-orthogonal multiple access, and Long Term Evolution on unlicensed spectrum. For each technique, we present the basic principle and research methodology of the state of the art. By considering various promising evolutions in 5G networks, we emphasize challenges to deploy each technique. Finally, we discuss the integration issue of multiple spectrum sharing techniques and identify potential challenges.
267 citations
TL;DR: In this article, the authors review some of the most stringent design challenges for the Tactile Internet and propose first avenues for specific solutions to enable the tactile Internet revolution, as well as propose first solutions for specific applications.
Abstract: Prior Internet designs encompassed the fixed, mobile, and lately the "things" Internet. In a natural evolution to these, the notion of the Tactile Internet is emerging, which allows one to transmit touch and actuation in real-time. With voice and data communications driving the designs of the current Internets, the Tactile Internet will enable haptic communications, which in turn will be a paradigm shift in how skills and labor are digitally delivered globally. Design efforts for both the Tactile Internet and the underlying haptic communications are in its infancy. The aim of this article is thus to review some of the most stringent design challenges, as well as propose first avenues for specific solutions to enable the Tactile Internet revolution.
TL;DR: The proposed slicing solutions involve the partition(s) of the core network and the radio access network resources, as well as configuration of the vehicular end-device functionality, to support different vehicle-to-everything use cases.
Abstract: The multitude of key vertical markets targeted by 5G networks calls for the support of multiple network slices on a common and programmable infrastructure. A network slice is intended as a collection of logical network functions and parameter configurations tailored to support the requirements of a particular service. In this article, we present our vision on the design of 5G network slice(s) customized for vehicle-to-everything services, which involve vehicles exchanging data with each other, with the infrastructure and any communicating entity for improved transport fluidity, safety, and comfort on the road. The suggested slicing solutions involve the partition(s) of the core network and the radio access network resources, as well as configuration of the vehicular end-device functionality, to support different vehicle-to-everything use cases. This research article aims to elaborate on the technological options and enablers, concerns, and challenges for the succesful deployment of 5G slice(s) for multitenant vehicle-to-everything services.
TL;DR: Three major advanced approaches whose adoption could increase the performance of future WPCN are presented: backscatter communications with energy harvesting; duty-cycle based energy management; and transceiver design for self-sustainable communications.
Abstract: Current wireless and cellular networks are destined to undergo a significant change in the transition to the next generation of network technology. The so called wireless powered communication network (WPCN) has been recently emerging as a promising candidate for achieving the target performance of future networks. According to this paradigm, nodes in a WPCN can be equipped with hardware capable of harvesting energy from wireless signals, that is, their battery can be ubiquitously replenished without physical connections. Recent technological advances in the field of wireless power harvesting and transfer are providing strong evidence of the feasibility of this vision, especially for low-power devices. The future deployment of WPCN is more and more concretely foreseen. The aim of this article is therefore to provide a comprehensive review of the basics and backgrounds of WPCN, current major developments, and open research issues. In particular, we first give an overview of WPCN and its structure. We then present three major advanced approaches whose adoption could increase the performance of future WPCN: backscatter communications with energy harvesting; duty-cycle based energy management; and transceiver design for self-sustainable communications. We discuss implementation perspectives and tools for WPCN. Finally, we outline open research problems for WPCN.
TL;DR: A critical analysis of the state-of-the-art EE-maximization techniques for hybrid MM systems allows us to identify several open research problems which, if addressed, will immensely help operators in planning for energy- efficient 5G deployments.
Abstract: As we make progress toward the 5G of wireless networks, the bit-per-joule energy efficiency (EE) becomes an important design criterion for sustainable evolution. In this regard, one of the key enablers for 5G is massive multiple-input multiple-output (MIMO) technology, where the BSs are equipped with an excess of antennas to achieve multiple orders of spectral and energy efficiency gains over current LTE networks. Here, we review and present a comprehensive discussion on techniques that further boost the EE gains offered by massive MIMO (MM). We begin with an overview of MM technology and explain how realistic power consumption models should be developed for MM systems. We then review prominent EE-maximization techniques for MM systems and identify a few limitations in the state-of-the-art. Next, we investigate EE-maximization in "hybrid MM systems," where MM operates alongside two other promising 5G technologies: millimeter wave and heterogenous networks. Multiple opportunities open up for achieving larger EE gains than with conventional MM systems because massive MIMO benefits mutually from the co-existence with these 5G technologies. However, such a co-existence also introduces several new design constraints, making EE-maximization non-trivial. A critical analysis of the state-of-the-art EE-maximization techniques for hybrid MM systems allows us to identify several open research problems which, if addressed, will immensely help operators in planning for energy- efficient 5G deployments.
TL;DR: In this article, a D2D Crowd framework for 5G mobile edge computing is proposed, where a massive crowd of devices at the network edge leverage network-assisted D2DM collaboration for computation and communication resource sharing.
Abstract: In this article we propose a novel D2D Crowd framework for 5G mobile edge computing, where a massive crowd of devices at the network edge leverage network-assisted D2D collaboration for computation and communication resource sharing. A key objective of this framework is to achieve energy-efficient collaborative task executions at the network edge for mobile users. Specifically, we first introduce the D2D Crowd system model in detail, and then formulate the energy-efficient D2D Crowd task assignment problem by taking into account the necessary constraints. We next propose a graph-matching-based optimal task assignment policy, and further evaluate its performance through extensive numerical study, which shows superior performance of more than 50 percent energy consumption reduction over the case of local task executions. Finally, we also discuss the directions of extending the D2D Crowd framework by taking into account a variety of application factors.
TL;DR: A scalable and flexible massive MIMO precoding scheme by exploiting the null-space of user signals is proposed, capable to effectively alleviate the interference to victim users and support high QoS as well as spectral efficiency.
Abstract: Scalability and flexibility are widely considered as two major design goals for 5G networks. Aiming at these goals, this article first identifies a promising architecture based on the heterogeneous cloud radio access network (H-CRAN), reviews the challenges in MIMO precoding for H-CRAN, and then proposes a scalable and flexible massive MIMO precoding scheme by exploiting the null-space of user signals. Specifically, the system can accomplish effective radio resource management and flexible spatial coordination by distinguishing the intended and victim users' CSI, and avoid the interference by precoding within the null-space for the CSI of victim users. Simulation results indicate that the proposed scheme is capable to effectively alleviate the interference to victim users and support high QoS as well as spectral efficiency.
TL;DR: A novel architecture for task selection and scheduling at the edge of the network using container-as-a-service (CoaaS) is presented and a multi-objective function is developed in order to reduce the energy consumption and makespan by considering different constraints such as memory, CPU, and the user's budget.
Abstract: In the last few years, we have witnessed the huge popularity of one of the most promising technologies of the modern era: the Internet of Things. In IoT, various smart objects (smart sensors, embedded devices, PDAs, and smartphones) share their data with one another irrespective of their geographical locations using the Internet. The amount of data generated by these connected smart objects will be on the order of zettabytes in the coming years. This huge amount of data creates challenges with respect to storage and analytics given the resource constraints of these smart devices. Additionally, to process the large volume of information generated, the traditional cloud-based infrastructure may lead to long response time and higher bandwidth consumption. To cope up with these challenges, a new powerful technology, edge computing, promises to support data processing and service availability to end users at the edge of the network. However, the integration of IoT and edge computing is still in its infancy. Task scheduling will play a pivotal role in this integrated architecture. To handle all the above mentioned issues, we present a novel architecture for task selection and scheduling at the edge of the network using container-as-a-service (CoaaS). We solve the problem of task selection and scheduling by using cooperative game theory. For this purpose, we developed a multi-objective function in order to reduce the energy consumption and makespan by considering different constraints such as memory, CPU, and the user's budget. We also present a real-time internal and external container migration technique for minimizing the energy consumption. For task selection and scheduling, we have used lightweight containers instead of the conventional virtual machines to reduce the overhead and response time as well as the overall energy consumption of fog devices, that is, nano data centers (nDCs). Our empirical results demonstrate that the proposed scheme reduces the energy consumption and the average number of SLA violations by 21.75 and 11.82 percent, respectively.
TL;DR: An effective bandwidth concept is introduced that ties the high system capacity, long battery life, and wide coverage goals together with the transmission bandwidth, such that these contradicting goals are balanced for best overall system performance.
Abstract: LPWAN is a type of wireless telecommunication network designed to allow long range communications with relaxed requirements on data rate and latency between the core network and a high-volume of battery-operated devices This article first reviews the leading LPWAN technologies on both unlicensed spectrum (SIGFOX, and LoRa) and licensed spectrum (LTE-M and NB-IoT) Although these technologies differ in many aspects, they do have one thing in common: they all utilize the narrow-band transmission mechanism as a leverage to achieve three fundamental goals, that is, high system capacity, long battery life, and wide coverage This article introduces an effective bandwidth concept that ties these goals together with the transmission bandwidth, such that these contradicting goals are balanced for best overall system performance
TL;DR: The RAN slicing problem in a multi-cell network in relation to the RRM functionalities that can be used as a support for splitting the radio resources among the RAN slices is analyzed.
Abstract: Network slicing is a fundamental capability for future 5G networks to properly support current and envisioned future application scenarios. Network slicing facilitates a cost-effective deployment and operation of multiple logical networks over a common physical network infrastructure such that each network is customized to best serve the needs of specific applications (e.g., mobile broadband, Internet of Things applications) and/or communications service providers (e.g., special purpose service providers for different sectors such as public safety, utilities, smart city, and automobiles). Slicing a RAN becomes particularly challenging due to the inherently shared nature of the radio channel and the potential influence that any transmitter may have on any receiver. In this respect, this article analyzes the RAN slicing problem in a multi-cell network in relation to the RRM functionalities that can be used as a support for splitting the radio resources among the RAN slices. Four different RAN slicing approaches are presented and compared from different perspectives, such as the granularity in the assignment of radio resources and the degrees of isolation and customization.
TL;DR: IEEE 802.11ax, a new standard being developed by the IEEE802.11 Working Group, is introduced, which will enable efficient usage of spectrum along with an enhanced user experience within high density WLAN networks.
Abstract: The popularity of IEEE 802.11 based wireless local area networks (WLANs) has increased significantly in recent years because of their ability to provide increased mobility, flexibility, and ease of use, with reduced cost of installation and maintenance. This has resulted in massive WLAN deployment in geographically limited environments that encompass multiple overlapping basic service sets (OBSSs). In this article, we introduce IEEE 802.11ax, a new standard being developed by the IEEE 802.11 Working Group, which will enable efficient usage of spectrum along with an enhanced user experience. We expose advanced technological enhancements proposed to improve the efficiency within high density WLAN networks and explore the key challenges to the upcoming amendment.
TL;DR: A big data computing architecture for smart grid analytics, which involves data resources, transmission, storage, and analysis, and a hybrid approach is adopted for the optimization including GA for storage planning and a game theoretic inner optimization for daily energy scheduling.
Abstract: The development of smart grid brings great improvement in the efficiency, reliability, and economics to power grid. However, at the same time, the volume and complexity of data in the grid explode. To address this challenge, big data technology is a strong candidate for the analysis and processing of smart grid data. In this article, we propose a big data computing architecture for smart grid analytics, which involves data resources, transmission, storage, and analysis. In order to enable big data computing in smart grid, a communication architecture is then described consisting of four main domains. Key technologies to enable big-data-aware wireless communication for smart grid are investigated. As a case study of the proposed architecture, we introduce a big-data- enabled storage planning scheme based on wireless big data computing. A hybrid approach is adopted for the optimization including GA for storage planning and a game theoretic inner optimization for daily energy scheduling. Simulation results indicate that the proposed storage planning scheme greatly reduce
TL;DR: This work proposes 5G-enabled software defined vehicular networks (5G-SDVNs), where software defined networking is exploited to dynamically manage VNGs in 5G and vehicular environment and uses the universal plug-andplay standard to enable scalable VNG networking.
Abstract: To meet the ever increasing demand of mobile data traffic, 5G enabling technologies are proposed in vehicular networks. Network densification is one of the key 5G technologies for large user throughput and traffic capacity, but there is a great challenge to serve numerous vehicular neighbors. According to observations from a real dataset of vehicles, we discover vehicular neighbor groups (VNGs) consisting of groups of vehicular neighbors. VNGs are crucial to enrich and enhance various services in 5G networks through efficient management. Therefore, we propose 5G-enabled software defined vehicular networks (5G-SDVNs), where software defined networking is exploited to dynamically manage VNGs in 5G and vehicular environment. Furthermore, we leverage mobile edge computing to strengthen network control of 5G-SDVN. By combining software defined networking with mobile edge computing, a programmable, flexible, and controllable network architecture is introduced for 5G-SDVN. The architecture simplifies network management, improves resource utilization, and achieves sustainable network development. We use the universal plug-andplay standard to enable scalable VNG networking. A case study of vehicular cloud computing highlights the advantages of 5G-SDVN. Finally, we also identify and discuss open issues in 5G-SDVN.
TL;DR: In this article, the authors investigated the applicability of NOMA in supporting cellular V2X services to achieve low latency and high reliability in the conventional OFDM-based LTE network.
Abstract: Benefiting from widely deployed infrastructure, the LTE network has recently been considered as a promising candidate to support vehicle-to-everything (V2X) services. However, with a massive number of devices accessing the V2X network in the future, the conventional OFDM-based LTE network faces congestion issues due to its low efficiency of orthogonal access, resulting in significant access delay and posing a great challenge especially to safety-critical applications. The non-orthogonal multiple access (NOMA) technique has been well recognized as an effective solution for the future 5G cellular networks to provide broadband communications and massive connectivity. In this article, we investigate the applicability of NOMA in supporting cellular V2X services to achieve low latency and high reliability. Starting with a basic V2X unicast system, a novel NOMAbased scheme is proposed to tackle the technical hurdles in designing high spectrally efficient scheduling and resource allocation schemes in the ultra-dense topology. We then extend it to a more general V2X broadcasting system. Other NOMA-based extended V2X applications and some open issues are also discussed.
TL;DR: In this article, a paradigm shift of wireless security to the surveillance and intervention of infrastructure-free suspicious and malicious wireless communications, by exploiting legitimate eavesdropping and jamming jointly, is presented.
Abstract: Conventional wireless security assumes wireless communications are legitimate, and aims to protect them against malicious eavesdropping and jamming attacks. However, emerging infrastructure- free mobile communication networks can be illegally used (e.g., by criminals or terrorists) but are difficult to monitor, thus imposing new challenges in public security. To tackle this issue, this article presents a paradigm shift of wireless security to the surveillance and intervention of infrastructure-free suspicious and malicious wireless communications, by exploiting legitimate eavesdropping and jamming jointly. In particular, proactive eavesdropping (via jamming) is proposed to intercept and decode information from suspicious communication links for the purpose of inferring their intentions and deciding further measures against them. Cognitive jamming (via eavesdropping) is also proposed to disrupt, disable, and even spoof the targeted malicious wireless communications to achieve various intervention tasks.
TL;DR: A novel framework of a content-centric vehicular network (CCVN) that is able to deliver contents more efficiently and outperforms the existing method is presented.
Abstract: Due to the expanding scale of vehicles and the new demands of multimedia services, current vehicular networks face challenges to increase capacity, support mobility, and improve QoE. An innovative design of next generation vehicular networks based on the content-centric architecture has been advocated recently. However, the details of the framework and related algorithms have not been sufficiently studied. In this article, we present a novel framework of a content-centric vehicular network (CCVN). By introducing a content-centric unit, contents exchanged between vehicles can be managed based on their naming information. Vehicles can send interests to obtain wanted contents instead of sending conventional information requests. Then we present an integrated algorithm to deliver contents to vehicles with the help of content-centric units. Contents can be stored according to their priorities determined by vehicle density and content popularity. Pending interests are updated based on the analysis of transmission ratio and network topology. The location of a content-centric unit to provide content during the moving of vehicles is determined by the forwarding information. Finally, simulation experiments are carried out to show the efficiency of the proposed framework. Results indicate that the proposed framework outperforms the existing method and is able to deliver contents more efficiently.
TL;DR: A discussion of the inherent technical challenges of BS ON-OFF switching and a comprehensive review of recent advances on switching mechanisms in different application scenarios are provided.
Abstract: To achieve the expected 1000x data rates under the exponential growth of traffic demand, a large number of BSs or APs will be deployed in 5G wireless systems to support high data rate services and to provide seamless coverage. Although such BSs are expected to be small-scale with lower power, the aggregated energy consumption of all BSs would be remarkable, resulting in increased environmental and economic concerns. In existing cellular networks, turning off the underutilized BSs is an efficient approach to conserve energy while preserving the QoS of mobile users. However, in 5G systems with new physical layer techniques and highly heterogeneous network architecture, new challenges arise in the design of BS ON-OFF switching strategies. In this article, we begin with a discussion of the inherent technical challenges of BS ON-OFF switching. We then provide a comprehensive review of recent advances on switching mechanisms in different application scenarios. Finally, we present open research problems and conclude the article.
TL;DR: Simulation results show that the proposed FRAN architecture and the associated mobility and resource management mechanisms can reduce the signaling cost and increase the net utility for the RAN.
Abstract: In order to make Internet connections ubiquitous and autonomous in our daily lives, maximizing the utilization of radio resources and social information is one of the major research topics in future mobile communication technologies. FRAN is regarded as a promising paradigm for the fifth generation of mobile networks. FRAN integrates fog computing with RAN and makes full use of the edge of networks. FRAN would be different in networking, computing, storage, and control compared to conventional RAN and the emerging cloud RAN. In this article, we provide a description of the FRAN architecture, and discuss how the distinctive characteristics of FRAN make it possible to efficiently alleviate the burden on the fronthaul, backhaul, and backbone networks, as well as reduce content delivery latencies. We focus on the mobility management, interference mitigation, and resource optimization in FRAN. Our simulation results show that the proposed FRAN architecture and the associated mobility and resource management mechanisms can reduce the signaling cost and increase the net utility for the RAN.
TL;DR: The experiments were carried out using an early-standard-compliant prototype based on a software defined radio partial implementation of NB-IoT that runs on a desktop computer connected to the network and it is found that a cloud radio access network is a good candidate for NB- IoT implementation.
Abstract: The 3GPP has introduced a new narrowband radio technology called narrowband Internet of Things (NB-IoT) in Release 13. NB-IoT was designed to support very low power consumption and low-cost devices in extreme coverage conditions. NB-IoT operates in very small bandwidth and will provide connectivity to a large number of low-data-rate devices. This article highlights some of the key features introduced in NB-IoT and presents performance results from real-life experiments. The experiments were carried out using an early-standard-compliant prototype based on a software defined radio partial implementation of NB-IoT that runs on a desktop computer connected to the network. It is found that a cloud radio access network is a good candidate for NB-IoT implementation.
TL;DR: This article reports the low-cost implementation of GPS spoofing attack and WiFi attack on UAVs, and suggests solutions to them.
Abstract: Communication security is critically important for the success of Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in military and civilian applications, they often carry sensitive information that adversaries might try to get hold of. While UAVs consist of various modules to enable them to function properly, potential security vulnerabilities may also exist in those modules. For example, by launching a GPS spoofing attack or WiFi attack, adversaries can capture the targeted UAV and access the sought after information. In fact, it has become easy to launch such attacks. In this article, we report our low-cost implementation of these attacks and suggest solutions to them.
TL;DR: This work proposes a novel TERG to precisely describe the evolution of multi-dimensional resources in BSN, and reveals the continuity and correlation relationships among various resources, and proposes an optimal resource allocation strategy to facilitate efficient cooperation amongVarious resources.
Abstract: Traditional satellite networks are generally locked down to a specific space mission, with isolated substrate infrastructure as well as network resources. This forbids dynamic resource sharing among different networks, and thus leads to resource under utilization, poor service provisioning and unacceptable expenditure. In this regard, it is crucial to embrace emerging technologies such as software-defined networking and network virtualization to construct a FRBSN. Both the resource management architecture and enabling strategies are explicitly investigated to realize FRBSN. Specifically, we propose a novel TERG to precisely describe the evolution of multi-dimensional resources in BSN, and reveal the continuity and correlation relationships among various resources. Based on TERG, we further propose an optimal resource allocation strategy to facilitate efficient cooperation among various resources. The achievable performance limits are demonstrated by simulations under a realistic BSN setting.