Utilization of flying platforms like Unmanned Aerial Vehicles (UAVs) is progressively increasing in our daily lives. Key characteristics such as flexibility, mobility and adaptive altitude, make UAVs particularly suitable for application in areas such as crop management, goods delivery, public safety and real-time video surveillance of public places to assist in terrestrial networks. IEEE 802.11ah

A high precision time delay calibration system based on optical fiber switches and fiber coils network for the satellite range measurement system is proposed in this paper. To reach the high time delay precision, the Phase Stabilized Optical Fiber (PSOF), is proposed to use as time delay component instead of the Single Mode Fiber (SMF) to minimize the temperature dependence of transmission delay time

Objective intelligibility assessment of dysarthric speech can assist clinicians in diagnosis of speech disorders as well as in medical treatment. This study investigates the use of glottal parameters (i.e. parameters that describe the acoustical excitation of voiced speech, the glottal flow) in the automatic intelligibility assessment of dysarthric speech. Instead of directly predicting the intelligibility

The electrolarynx (EL) is an electromechanical device that enables patients to produce voice following the surgical removal of their larynx. The purpose of this study is to understand the acoustic and perceptual characteristics of Mandarin consonants produced by EL speakers. First, the acoustic characteristics (including speech intensity, consonant duration, spectral peak, and F2 onset) of Mandarin

In this paper, we investigate the application of graph signal processing (GSP) theory in speech enhancement. We first propose a set of shift operators to construct graph speech signals, and then analyze their spectrum in the graph Fourier domain. By leveraging the differences between the spectrum of graph speech and graph noise signals, we further propose the graph spectral subtraction (GSS) method

With the rapid development of the power infrastructures and the increase in the number of electric vehicles (EVs), vehicle-to-grid (V2G) technologies have attracted great interest in both academia and industry as an energy management technology in 5G smart grid. Considering the inherently high mobility and low reliability of EVs, it is a great challenge for the smart grid to provide on-demand services

In this paper, a non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) system is proposed, where paired users (the mth user and the nth user) offload tasks to the MEC server under imperfect channel state information (ipCSI) condition. To evaluate the effect on performance under ipCSI condition in NOMA-MEC system, this study derives new exact and asymptotic expressions of the offloading

NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search for the optimum value of such NP-hard optimization problems, given the problem can be embedded on their hardware. However, this is often not possible due

Memristors play a vital role in the design of high density and low power memory devices. Considering the complex behaviour of memristor devices because of the feature that its memductance changes with the input current, these devices finds its applications in design of nonlinear circuits. Similarly, Josephson junction resonators also exhibit complex behaviours because of its inductive properties. To

In this work, we present a new method for the direction-of-arrival (DOA) estimation of coherent sources using a symmetric uniform linear array (ULA) without prior source number information. The proposed method constructs a new cost function based on the joint diagonalization structure of the Toeplitz matrix. The estimation of DOAs is made by developing a new spatial spectrum via a 1-D search. Furthermore

The Heterogeneous Cellular Network (HCN) paradigm holds promise for increasing the coverage probabilities and date rates of its users. The concept of downlink and uplink decoupling (DUDe) has been extensively investigated to alleviate the load imbalance problem in HCNs. Furthermore, the dual connectivity (DC) access scheme, which allows user equipment (UE) to simultaneously connect with multiple base

This paper, investigates and presents the optimal parameter identification of digital pre-distortion (DPD) models for radio frequency power amplifiers (RF PAs) using a modified differential evolution (MDE) based optimization algorithm. Compared to the conventional exhaustive search method which is computationally intensive, our proposed approach enables the identification of a best-fit DPD model from

The important role provided by relays in communication networks is indisputable as they improve the transmission robustness by the retransmission schemes. In this paper, the effective capacity of two-way relay channels (TWRCs) in presence of retransmission schemes is investigated. We derive the effective capacity for the two phase scheme referred to as complex field network coding (CFNC). Based on

The analysis and design trade-offs of a simple and economical technique to implement wideband low-voltage CMOS instrumentation amplifiers (IAs) based on indirect current feedback (ICF), are described. The input and an output transconductors consist of two super-source-followers and a resistor. As a result, the overall performance of the IA is enhanced. A thorough analysis of the proposed technique

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Learning from massive network data to produce cognitive knowledge for efficient resource management in 5G and beyond 5G (B5G) is still challenging. We are delighted to introduce the readers to this special section of the IEEE Transactions on Cognitive Communications and Networking (TCCN), which aims at exploring recent advances and addressing practical challenges in the intelligent resource management

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Deep learning based intelligent intrusion detection (IID) methods have been received strongly attention for computer security protection in cybersecurity. All these learning models are trained at either a single user server or centralized server. For one thing, it is almost impossible to train a powerful deep learning model at a single user. For other, it will encounter intrusion risks at center server

Frequency allocation in small cell-based green heterogeneous mobile networks is a demanding research domain nowadays. Femtocells are the essential components of small cell networks. In this paper, we propose a low power micro-femtocell network using the master–slave algorithm. In the master–slave algorithm, the master node allocates work to the slave nodes. When a slave ends its task given by a master

In this letter, we are proposing $Bo$ CNN architecture framework for occluded thermal face recognition. We analyzed the performance of Pretrained models using transfer learning and they exhibit promising results for thermal faces without occlusion. The performance degrades with occlusion. We have used different decision level fusion strategies post transfer learning for the performance enhancement

A fast and effective image fusion method based on discrete cosine transform (DCT) is proposed. The fusion quality and computation time of current DCT-based image fusion methods largely depend on the selected block size, and the selection of the block size is very difficult in practice. A novel image fusion method based on DCT coefficient matrix features is proposed, which can effectively overcome the

This paper develops a framework for the design of diffusion adaptive algorithms, where a network of nodes aim to estimate system parameters from the collected distinct local data stream. We explore the time and spatial knowledge of system responses and model their evolution in both time and spatial domain. A weighted maximum a posteriori probability (MAP) is used to derive an adaptive estimator, where

In this letter, we propose a novel conjugate gradient (CG) adaptive filtering algorithm for online estimation of system responses that admit sparsity. Specifically, the Sparsity-promoting Conjugate Gradient (SCG) algorithm is developed based on iterative reweighting methods popular in the sparse signal recovery area. We propose an affine scaling transformation strategy within the reweighting framework

Analytic dynamic models for target estimation are often approximations of the potentially complex behaviour of the object of interest. Its true motion might depend on hundreds of parameters and can involve long-term temporal correlation. However, conventional models keep the degrees of freedom low and they usually assume the Markov property to reduce computational complexity. In particular, the Kalman

Spectrum sensing is one of the key technologies in the field of cognitive radio, which has been widely studied. Among all the sensing methods, energy detection is the most popular because of its simplicity and no requirement of any prior knowledge of the signal. In the case of low signal-to-noise ratio (SNR), the traditional double-threshold energy detection method employs fixed thresholds and there

In the scenario of mobile fog computing (MFC), communication between vehicles and fog layer, which is called vehicle-to-fog (V2F) communication, needs to use bandwidth resources as much as possible with low delay and high tolerance for errors. In order to adapt to these harsh scenarios, there are important technical challenges concerning the combination of network coding (NC) and multipath transmission

Wireless power transfer techniques to transfer energy have been widely adopted by wireless rechargeable sensor networks (WRSNs). These techniques are aimed at increasing network lifetime by transferring power to end devices. Under these wireless techniques, the incurred charging latency to replenish the sensor nodes is considered as one of the major issues in wireless sensor networks (WSNs). Existing

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5G is raising high expectations, offering new avenues for research, and paving the way to a safer and highperforming set of innovative use-cases. For use-cases related for instance to Internet of Things (IoT), self-driving vehicles, or unmanned aerial vehicles (UAVs), the programming and management of the underlying network resources will be carried out in a dynamic and scalable manner. In this vein

The prevailing wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Unfortunately, bugs, misconfigurations, faults or attacks can introduce inconsistencies between the network control and the data plane that can undermine the correct operation at runtime. Through our experiments

Software-Defined Networking (SDN) is an innovational network architecture which gives network administrators the ability to directly control the whole network by programming on a centralized controller. Due to network complexity, networks are unlikely to be bug-free. The ability to verify data plane properties will make network management easier for network administrators in SDN. In this paper, we

Software-Defined Networking (SDN) enables more dynamic and fine-grained network control. In particular, network operators can route traffic not only based on packet header fields, but also higher-level parameters such as user settings, traffic characteristics, and application-layer information extracted by virtualized network functions such as DPI, firewall and authentication servers. Integrating these

In this paper, we study the problem of data flow management in the presence of heterogeneous flows — elephant and mice flows — in software-defined networks (SDNs). Most of the researchers considered the homogeneous flows in SDN in the existing literature. The optimal data flow management in the presence of heterogeneous flows is NP-hard. Hence, we propose a game theory-based heterogeneous data flow

In this paper, we present an open source Software-Defined Networking (SDN) based emulation platform called Timber . We aim to provide the research community with an experimental tool for the design and evaluation of the new Quality of Experience (QoE) management and monitoring procedures for video streaming. To this aim, the main functionalities of Timber include: i) an SDN application for taking QoE-aware

Envisioned 5G applications and services, such as Tactile Internet, Industry 4.0 use-cases, remote control of drone swarms, pose serious challenges to the underlying networks and cloud platforms. On the one hand, evolved cloud infrastructures provide the IT basis for future applications. On the other hand, networking is in the middle of a momentous revolution and important changes are mainly driven

Programmable data planes, PDPs, enable an unprecedented level of flexibility and have emerged as a promising alternative to existing data planes. Despite the rapid development and prototyping cycles that PDPs promote, the existing PDP ecosystem lacks appropriate abstractions and algorithms to support these rapid testing and deployment life-cycles. In this paper, we propose P4Visor, a lightweight virtualization

5G RAN aims to evolve new technologies spanning the Cloud infrastructure, virtualization techniques and Software Defined Network capabilities. Advanced solutions are introduced to split the functions of the Radio Access Network (RAN) between centralized and distributed locations. Such paradigms improve RAN flexibility and reduce the infrastructure deployment cost without impacting the user quality

Network function virtualization (NFV) of IP Multimedia Subsystem (IMS) pose promise to service increasing multimedia traffic demand. In this paper, we show that virtualized IMS (vIMS) is unable to provide session-level resilience under faults and becomes the bottleneck to high service availability. We propose a design to provide fault-tolerance for vIMS operations. In control-plane, our system decomposes

Online social networks (OSNs) are emerging as the most popular mainstream platform for content cascade diffusion. In order to provide satisfactory quality of experience (QoE) for users in OSNs, much research dedicates to proactive content placement by using the propagation pattern, user’s personal profiles and social relationships in open social network scenarios (e.g., Twitter and Weibo). In this

Network slicing, as a key 5G enabling technology, is promising to support with more flexibility, agility, and intelligence towards the provisioned services and infrastructure management. Fulfilling these tasks is challenging, as nowadays networks are increasingly heterogeneous, dynamic and large-dimensioned. This contradicts the dominant network slicing solutions that only customize immediate performance

As a novel sensing paradigm, crowdsensing has gained great attention due to large-scale user participation, low cost and wide data source, replacing traditional sensor based sensing in intelligent transportation, environmental monitoring, urban public management, etc. In crowdsensing, however, user privacy leakage is a common but fatal problem, where the participants in crowdsensing might not provide

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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In order to enhance the physical-layer security of the communication systems in the optical fiber channel, a novel secure communication scheme based on optical code-division multiple-access (OCDMA) technology is proposed and its physical-layer security is quantitatively analyzed. Due to the small capacity of the traditional OCDMA codewords, the address code used by legitimate user is vulnerable to

Video-based human motion analysis is an important research direction in the field of computer vision. It detects moving objects from video sequences, extracts key parts of the human body, and obtains useful information for human movements. In this paper, the joints of the teeing arm are first color-coded. The tennis teeing video is collected by a high-speed camera. The coordinates of the tacking points

Non-orthogonal multiple access (NOMA) with power domain multiplexing and successive interference cancellation (SIC) is one of the promising technologies for future wireless communication. The performance of NOMA is highly dependent on resource allocation such as power allocation and channel assignment. In this paper, we investigate the power allocation (PA) scheme, to optimize the weighted maximin

Super-resolution reconstruction technology has important scientific significance and application value in the field of image processing by performing image restoration processing on one or more low-resolution images to improve image spatial resolution. Based on the SCSR algorithm and VDSR network, in order to further improve the image reconstruction quality, an image super-resolution reconstruction

Very recently, with the widespread research of deep learning, its achievements are increasingly evident in image inpainting tasks. However, many existing methods fail to effectively reconstruct vivid contents and refine structures. In order to solve this issue, in this paper, a novel two-stage generative adversarial network based on the fusion of edge structures and color aware maps is proposed. In

Systems engineering (SE) and model‐based development (MBD) attract attention from manufacturers to produce more complex products with less rework in order to satisfy higher demands. However, concrete methodology is not defined well. This paper proposes a methodology of target assignment with respect to a special functional cascading for integrated atchitectural products. This paper also proposes “abstracted

In this paper, an internally compensated dual-summed flipped voltage follower (FVF) low drop-out (LDO) regulator is proposed. This LDO uses a small miller capacitance (MC) and an active feed-forward compensation (AFFC) to internally stabilize the feedback loop. The active feed-forward compensator shifts an RHP zero of the miller capacitance to the load-dependent LHP zero. A simple RC high-pass filter

A multi-band, high gain, miniaturized fractal microstrip antenna is described in this article for modern communication systems. Space-utilizing and structure-similarity are the two main characteristics of fractal miniaturization technique. In the proposed design, a hexagonal Sierpinski gasket structure is loaded on a square microstrip antenna. Using fractal miniaturization techniques, the patch area