ALBERT

Description: Provides an overview of the technical articles and features presented in this issue.

Description: Presents the front cover for this issue of the publication.

Description: Six senior computer science educators answer questions about the current state of computer science education, software engineering, and licensing software engineers.

Description: Provides a listing of current staff, committee members and society officers.

Description: The Internet of Things is a new department with the mission of presenting fresh ideas and applications from a practitioner point of view. The authors are interested in showcasing articles about real, implemented Internet of Things (IoT) systems.

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Description: The Industrial Internet of Things is growing fast. But the rapid growth of IIoT devices raises a number of security concerns, because the IIoT device is weak in defending against malware, and the method of managing a large number of IIoT devices is awkward and inconvenient. This article proposes a multi-level DDoS mitigation framework (MLDMF) to defend against DDoS attacks for IIoT, which includes the edge computing level, fog computing level, and cloud computing level. Software defined networking is used to manage a large number of IIoT devices and to mitigate DDoS attacks in IIoT. Experimental results show the effectiveness of the proposed framework.

Description: Commemorating the 20th anniversary of IT Professional, the advisory board chair and four past editors in chief reflect on the first two decades of the magazine.

Description: In a case study where a Dutch small-to-medium enterprise (SME) implemented test-driven development and continuous integration, researchers observed that the SME discovered a higher number of defects compared to a baseline case study, and that there was an increase in the focus on quality and test applications.

Description: By providing access to data from numerous systems in one database and supporting the systems that can produce an appropriate customer experience, a customer data platform overcomes the limitations imposed by fragmented point solutions and presents a holistic approach to customer interactions.

Description: An introduction to the new Life in the C-Suite column, which will help C-level executives understand the vast digital world in which they live, and how they should leverage digital technology into their business processes and business models.

Description: Student Forum is a new column that intends to connect IT students with industry, government, and academia.

Description: The new IT Economics department seeks to advance the understanding of various microeconomic and macroeconomic issues that IT managers need to examine in their decisions to adopt and implement information and communications technology-related systems, services, processes, and practices.

Description: Provides a listing of current committee members and society officers.

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

Description: The efficient integration of optical switching in data center networks is being studied as a means to cope with surging traffic demands. Optically switched, flatter network architectures more efficiently handle the east-west traffic profiles of modern data centers. Limitations in the port count and reconfiguration speed of optical switches require novel network designs offering network scalability and dynamicity. Interaction of the optically switched data plane with a software-defined control and orchestration framework, meeting current common practices in data centers, necessitates the design of custom network control algorithms and software modules as well as the integration of novel functionalities. The approach of the European project NEPHELE is presented, offering an endto- end solution that addresses the optical data plane, the control plane, and its interaction with the application layer.

Description: The comprehensive evolution of information communication technologies on mobile sensing objects has led to the provision of versatile ubiquitous network services embedded with specific- purpose modern sensors and intelligent wearable devices. The universal Internet connectivity of such smart objects has brought about a new era of ubiquitous application development for the Internet of Things. Meanwhile, security has become critically important. In the past decade, academia and industry have dedicated great efforts to the design of continuous authentication for multi-modal networks. Multiform authentication bio-tokens have been introduced for continuous entity identification and verification. With the rapid growth and universality of wearable devices, in this article we target continuous authentication for the IoT-based environment with users possessing wearable healthcare (and wellness) related smart objects. To present the state of the art, we provide a comprehensive review of continuous authentication in recent years. Critical characteristics of new biometrics are then introduced. Second, we present a wearable plantar bio-feature extractor constructed via commercial pressure sensors and the Raspberry PI platform. The prototype is adopted to retrieve user plantar bio-data as the raw (and training) data in the proposed authentication system. Third, we apply machinelearning- based techniques to derive a user's plantar bio-features as authentication tokens in the system to support continual (and real-time) entity verification in the background without the user's notice.

Description: In IoT-based healthcare, medical devices are more vulnerable to numerous security threats and attacks than other network devices. Current solutions are able to provide protection to patients' data during data transmission to some extent, but cannot prevent some sophisticated threats and attacks such as collusion attacks and data leakage. In this article, we first investigate the challenges with privacy protected data collection. Then we propose a practical framework called PrivacyProtector, patient privacy protected data collection, with the objective of preventing these types of attacks. PrivacyProtector includes the ideas of secret sharing and share repairing (in case of data loss or compromise) for patients' data privacy. Since it is the first time, we apply the Slepian- Wolf-coding-based secret sharing (SW-SSS) in PrivacyProtector. In the framework, we use a distributed database consisting of multiple cloud servers, which ensures that the privacy of patients' personal data can remain protected as long as one of the servers remains uncompromised. We also present a patient access control scheme in which multiple cloud servers collaborate in shared construction to offer patients' data to healthcare providers without revealing the content of the data. The privacy performance analysis has shown that the PrivacyProtector framework is secure and privacy-protected against various attacks.

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Description: Widespread use of white light-emitting diodes and ubiquitous smart devices offer the opportunity to establish VLC, which has become a hot research topic based on the growing number of publications over the last decade. Camera-based VLC, namely OCC, provides many unique features when compared to a single-photodiode-based system, such as the ability to separate incident light in the spatial and color domains. OCC technology represents a promising approach to utilize the benefits of VLC in beyond-5G scenarios and is one of the key technologies of the Internet of Things. Establishing a long communication channel in OCC, as well as non-flickering illumination by using low-frame-rate camera detectors, requires special modulation schemes. This article provides an overview of the principles of three categories of modulation schemes for OCC systems using a low-frame-rate camera detector. In addition, a series of undersampled modulation schemes are proposed and discussed to achieve flicker-free OCC with higher spectral efficiency. In addition, framing structures are designed to solve problems occurring in OCC systems using particular modulation schemes. To evaluate the performance of these modulation schemes, measured bit error rate values are shown. Finally, challenges in the implementation of OCC systems are also outlined.

Description: Equipped with an L-band radiometer, SMOS, and Aquarius provide an unprecedented sea surface salinity (SSS) dataset of the global oceans in days. The sensitivity of L-band brightness temperature (TB) to SSS variation is about 0.3–0.8 K/psu, which means the salinity signal in TB is very weak. Enormous efforts are devoted to the development, evaluation, and improvement of the SSS retrieval algorithm especially under some unfavorable conditions, i.e., the rain. Rain drops inducing freshening and roughness effects on the sea surface have made the SSS retrieval challenging for years. This paper describes a new method to separate the freshening and roughness effects of rainfall based on the combined active/passive observations of Aquarius. The dependence of the sea surface emissivity (sensitive to both roughness and freshening) on the backscatter (only sensitive to roughness) is obtained and the rain-induced roughness is corrected. The method is applied to the salinity retrieval under rain. The retrieval results ( $text{SSS}_{rc}$ ) are compared with HYCOM data corrected by the rain impact model ( $text{SSS}_{text{HYCOM}_text{RIM}}$ ). The bias of $text{SSS}_{text{rc}}$ shows no clear dependence on rain rate. However, the bias of the standard product of Aquarius ( $text{SSS}_{text{ADPS}}$ , V4.0) rises sharply with rain rate. Furthermore, the standard deviation of $text{SSS}_{text{rc}}$ is about 0.5 psu, which is also superior to $text{SSS}_{text{ADPS}}$ (0.9 psu). Th- above results confirm the feasibility of this new retrieval algorithm for the SSS remote sensing in rainy weather.

Description: This tutorial article presents an outline of image sensor communication (ISC) technologies realized by light sources and cameras. It discusses the revision of the IEEE 802.15.7-2011 standard, namely, the IEEE 802.15.7m Optical Wireless Communications Task Group, which has significantly influenced the development of the ISC technology. It also reviews the ISC technical proposals of the task group and compares them with related works. The essential technical considerations of the ISC specifications are presented, and the future directions of research and development are discussed.

Description: Arctic landfast sea ice is widely utilized for transportation by local communities and industry, with trafficability largely governed by ice roughness. Here, we introduce an approach to evaluate ice roughness that can aid in routing of ice roads and assessment of spatial variability and long-term changes in trafficability. Drawing on synthetic aperture radar (SAR) polarimetry, SAR interferometry (InSAR), and other remote sensing techniques, we integrated approaches into the trafficability assessment that had rarely been applied over sea ice in the past. Analysis of aerial photogrammetry obtained through structure-from-motion helped verify cm-scale accuracy of X-band InSAR-derived ridge height and link L-band polarimetric classification to specific roughness regimes. Jointly, these approaches enable a km-scale evaluation of ridge topography and cm- to m-scale roughness—both critical for the assessment of trafficability. A trafficability index was derived from such SAR data in conjunction with analysis of ice trail routing and ice use near Utqiaġvik, Alaska. The index identifies areas of reduced trafficability, associated with pressure ridges or rubble ice, and served to delineate favorable trail routes for different modes of transportation, with potential uses ranging from ice road routing to emergency evacuation. Community outreach is needed to explore how this approach could assist different ice users in reducing risk, minimizing trail or ice construction efforts, and improving safety.

Description: Yulong Mountain, which is the southernmost snowcapped mountain in mainland Eurasia, has been confronted with significant glacier recession in the last decades due to global climate warming. The recession of these small-scale monsoonal temperate glaciers is a sensitive indicator of global warming. However, there have been few studies that have comprehensively monitored the historical glacier recession in Yulong Mountain area. This paper integrates multisource remote sensing data to monitor the glacial status on Yulong Mountain between 1957 and 2009. Integrating a topographic map, the long-term observed Landsat TM/ETM+ images, and multitemporal digital elevation model datasets, both the area change and regional mass balance of the Yulong glaciers are analyzed. According to the results, the area of the Yulong glaciers decreased from 11.57 to 4.55 km 2 at a rate of −0.14 km 2 yr −1 over the last 52 years between 1957 and 2009. The 1987–1999 specific mass balance was −0.31 ± 0.33 m yr −1 water equivalent, while the 1987–2008 mass balance was −0.27 ± 0.35 m yr −1 water equivalent. It can be interpreted from the results that the Yulong glaciers have experienced persistent glacier recession during the last decades. The glacier melting is still significant due to the continuously rising temperature. Furthermore, spatially heterogeneous glacier recession has been observed in this area. The glacier changes are spatially varied, which is probably due to the local temperature and precipitation, the glacier sizes, the terminus altitudes, and terrain factors. The influencing elements interacted with each other, and the climate conditions are the dominant factors affecting glacier status.

Description: Sustainable development in metropolitan regions is challenging in the light of continuous urbanization. Remote sensing provides timely and reliable information on urban areas and their changing patterns. This study's objectives are to evaluate the contribution of Sentinel-2A (S-2A) data to urban ecosystem service mapping and to investigate spatial ecosystem service characteristics with landscape metrics through a novel method. Service pattern changes between 2005 and 2015 are mapped for Beijing, China. Landscape metrics are used to qualitatively evaluate urban ecosystem service provision bundle changes. S-2A and Landsat TM data are segmented and classified with SVM, distinguishing three artificial and four natural classes based on ecosystem function. Spatial characteristics influencing ecosystem services are quantified with seven landscape metrics. Beijing's urban development is characterized by reduction in agricultural areas in the urban fringe in favor of built-up areas, urban green space, and golf courses. A transformation of old suburban agglomerations into urban green space can be observed. The planar increase in urban areas is accompanied by the creation of managed urban green space. Service bundles based on land cover classes and spatial characteristics decreased more than 30% for bundles that represent food supply, noise reduction, waste treatment, and global climate regulation. Temperature regulation/moderation of climate extremes, recreation/place values/social cohesion, and aesthetic benefits/cognitive development are least affected. This new approach of extending the ecosystem service concept through integration of spatial characteristics of ecosystem service provisional patches through landscape metrics is believed to give a more realistic appraisal of ecosystem services in urban areas.

Description: Evapotranspiration (ET) is the combination process of the surface evaporation and plant transpiration, which occur simultaneously, and it links the terrestrial water cycles, carbon cycles, and energy exchange. In this study, based on the observations from 242 global FLUXnet sites, with daily mean temperature, relative humidity, net radiation, wind speed, incoming shortwave radiation, maximum temperature, minimum temperature, normalized difference vegetation index, altitude, difference in temperature, and observed ET as input data, we used a support vector machine and a semiempirical algorithm to estimate the land surface daily ET at nine different vegetation-type sites. Subsequently, based on the meteorological reanalysis data combined with remote sensing data, we estimated regional land surface ET of China during 1982–2010. The results showed that, for all vegetation-type sites, when the predicted ET was validated with the eddy covariance measurements, the support vector machine algorithm undervalued ET while the semiempirical algorithm overvalued ET. When five indicators and the second classification method were selected, the semiempirical algorithm probably could explain 56%–76% of the land surface ET change, whereas the support vector machine algorithm probably could explain 71%–85%. The regional values of annual daily average ET varied from 5.8 to 110.5 W/m 2 , and the land surface ET overall trend decreased from the southeast to the northwest in China.

Description: Synthetic aperture radar (SAR) imaging is a crucial tool in providing images of the earth's surface for military and civilian applications such as target surveillance and its classification. The precision of the application degrades with the presence of inherent speckle and poor resolution of images from the SAR image acquisition devices. Thus, the objective of the proposed method is to develop a technique to enhance the resolution while despeckling the inherent noise, simultaneously, since the conventional super resolution methods have failed to do the same. Moreover, the works from the literature that super resolve SAR images have also neglected the signal-dependent noise model. The work proposed in this paper significantly reduces the speckle and super resolves the SAR image using an Importance Sampling Unscented Kalman Filter framework that best models the non-linearity of the system. The technique has been assessed quantitatively and qualitatively on synthetic images as well as on real SAR images. The performance evaluation based on peak signal-to-noise-ratio, structural similarity index measure, feature similarity index measure, edge preservation factor, and equivalent number of looks values throw light on the superiority of the proposed method over the standard and other recent techniques. This can serve to generate images with a better reconstructive quality that would aid various applications in multidisciplinary domains.

Description: The limited modulation bandwidth of commercial light-emitting diodes (LEDs) is one of the critical bottlenecks for visible light communications. Possible approaches to increase the bandwidth include the use of micron sized LEDs, which can withstand higher current densities, as well as the use of LED structures that are grown on different crystal planes to the conventional polar c-plane. We compare c-plane InGaN/GaN LEDs with semipolar ( $11overline {2}2$ ) LEDs containing a 4- and 8-nm single quantum well. The modulation bandwidth of semipolar LEDs with active areas varying from $200times 200$ to $30times 30,,mu text{m}^{2}$ is shown to be governed by both current density and size. A small signal bandwidth of over 800 MHz for a relatively low applied current density of 385 A/cm 2 is reported for $30times 30 ,,mu text{m}^{2}$ LEDs with 8-nm thick quantum well. An optical link using an easy non-return-to-zero ON–OFF keying modulation scheme with a data rate of 1.5 Gb/s is demonstrated.

Description: A compact optical fiber sensor based on a Fabry–Perot interferometer (FPI) with an integrated fiber Bragg grating is proposed to measure pressure and temperature simultaneously. The light reflectors of the proposed FPI comprise a graphene film and a fiber end face. The sensitivities of the FPI sensor for measuring pressure and temperature are 501.4 nm/kPa and 306.2 nm/°C, respectively. Conflicting signals of pressure and temperature can cause cross-impact errors at 610 Pa/°C. The introduction of a fiber Bragg grating can effectively prevent the cross-impact of the FPI sensor. The pressure sensitivity obtained is 7.96 to 12 times higher than the previous study. The proposed fiber sensor can simultaneously measure pressure and temperature using a sensitivity matrix.

Description: Throughout the past few decades, the separable discrete cosine transform (DCT), particularly the DCT type II, has been widely used in image and video compression. It is well-known that, under first-order stationary Markov conditions, DCT is an efficient approximation of the optimal Karhunen–Loève transform. However, for natural image and video sources, the adaptivity of a single separable transform with fixed core is rather limited for the highly dynamic image statistics, e.g., textures and arbitrarily directed edges. It is also known that non-separable transforms can achieve better compression efficiency for images with directional texture patterns, yet they are computationally complex, especially when the transform size is large. In order to achieve higher transform coding gains with relatively low-complexity implementations, we propose a joint separable and non-separable transform. The proposed separable primary transform, named enhanced multiple transform (EMT), applies multiple transform cores from a pre-defined subset of sinusoidal transforms, and the transform selection is signaled in a joint block level manner. Moreover, a non-separable secondary transform (NSST) method is proposed to operate in conjunction with EMT. Unlike the existing non-separable transform schemes which require excessive amounts of memory and computation, the proposed NSST efficiently improves coding gain with much lower complexity. Extensive experimental results show that the proposed methods, in a state-of-the-art video codec, such as high efficiency video coding, can provide significant coding gains (average 6.9% and 4.5% bitrate reductions for intra and random-access coding, respectively).

Description: The capabilities of bistatic radar observations to estimate the wind field over the ocean are investigated in this paper. The work is based on the analysis of simulated data obtained through a well-established electromagnetic model, which accounts for the anisotropy of the ocean’s spectrum and of second-order effects of the scattering phenomenon. Both co-polarized and cross-polarized C-band numerical data, obtained considering monostatic and bistatic configurations, are exploited to investigate on the existence of optimal configurations able to minimize the wind vector error estimation. To this aim, the sensitivities of the bistatic normalized radar cross section with respect to both wind speed and direction are accurately investigated and exploited to evaluate the minimum achievable error standard deviation of the estimation. Small and large baselines are analyzed, giving particular emphasis to bistatic geometries constituted by one or two passive receivers aligned along the track defined by the active system. This investigation, originally performed in the framework of the SAOCOM-CS scientific satellite mission, is conceived to accurately assess the potentiality of bistatic observations of the ocean over variable baselines and to gather valuable information for the design of future bistatic satellite missions.

Description: The use of synthetic sequences is one of the most promising tools for advanced in silico evaluation of the quantification of cardiac deformation and strain through 3-D ultrasound (US) and magnetic resonance (MR) imaging. In this paper, we propose the first simulation framework which allows the generation of realistic 3-D synthetic cardiac US and MR (both cine and tagging) image sequences from the same virtual patient. A state-of-the-art electromechanical (E/M) model was exploited for simulating groundtruth cardiac motion fields ranging from healthy to various pathological cases, including both ventricular dyssynchrony and myocardial ischemia. The E/M groundtruth along with template MR/US images and physical simulators were combined in a unified framework for generating synthetic data. We efficiently merged several warping strategies to keep the full control of myocardial deformations while preserving realistic image texture. In total, we generated 18 virtual patients, each with synthetic 3-D US, cine MR, and tagged MR sequences. The simulated images were evaluated both qualitatively by showing realistic textures and quantitatively by observing myocardial intensity distributions similar to real data. In particular, the US simulation showed a smoother myocardium/background interface than the state-of-the-art. We also assessed the mechanical properties. The pathological subjects were discriminated from the healthy ones by both global indexes (ejection fraction and the global circumferential strain) and regional strain curves. The synthetic database is comprehensive in terms of both pathology and modality, and has a level of realism sufficient for validation purposes. All the 90 sequences are made publicly available to the research community via an open-access database.

Description: Collecting large databases of annotated medical images is crucial for the validation and testing of feature extraction, statistical analysis, and machine learning algorithms. Recent advances in cardiac electromechanical modeling and image synthesis provided a framework to generate synthetic images based on realistic mesh simulations. Nonetheless, their potential to augment an existing database with large amounts of synthetic cases requires further investigation. We build upon these works and propose a revised scheme for synthesizing pathological cardiac sequences from real healthy sequences. Our new pipeline notably involves a much easier registration problem to reduce potential artifacts, and takes advantage of mesh correspondences to generate new data from a given case without additional registration. The output sequences are thoroughly examined in terms of quality and usability on a given application: the assessment of myocardial viability, via the generation of 465 synthetic cine MR sequences (15 healthy and 450 with pathological tissue viability [random location, extent, and grade, up to myocardial infarct]). We demonstrate that: 1) our methodology improves the state-of-the-art algorithms in terms of realism and accuracy of the simulated images and 2) our methodology is well-suited for the generation of large databases at small computational cost.

Description: It is generally recognized that color information is central to the automatic and visual analysis of histopathology tissue slides. In practice, pathologists rely on color, which reflects the presence of specific tissue components, to establish a diagnosis. Similarly, automatic histopathology image analysis algorithms rely on color or intensity measures to extract tissue features. With the increasing access to digitized histopathology images, color variation and its implications have become a critical issue. These variations are the result of not only a variety of factors involved in the preparation of tissue slides but also in the digitization process itself. Consequently, different strategies have been proposed to alleviate stain-related tissue inconsistencies in automatic image analysis systems. Such techniques generally rely on collecting color statistics to perform color matching across images. In this work, we propose a different approach for stain normalization that we refer to as stain transfer. We design a discriminative image analysis model equipped with a stain normalization component that transfers stains across datasets. Our model comprises a generative network that learns data set-specific staining properties and image-specific color transformations as well as a task-specific network (e.g., classifier or segmentation network). The model is trained end-to-end using a multi-objective cost function. We evaluate the proposed approach in the context of automatic histopathology image analysis on three data sets and two different analysis tasks: tissue segmentation and classification. The proposed method achieves superior results in terms of accuracy and quality of normalized images compared to various baselines.

Description: In medical image analysis applications, the availability of the large amounts of annotated data is becoming increasingly critical. However, annotated medical data is often scarce and costly to obtain. In this paper, we address the problem of synthesizing retinal color images by applying recent techniques based on adversarial learning. In this setting, a generative model is trained to maximize a loss function provided by a second model attempting to classify its output into real or synthetic. In particular, we propose to implement an adversarial autoencoder for the task of retinal vessel network synthesis. We use the generated vessel trees as an intermediate stage for the generation of color retinal images, which is accomplished with a generative adversarial network. Both models require the optimization of almost everywhere differentiable loss functions, which allows us to train them jointly. The resulting model offers an end-to-end retinal image synthesis system capable of generating as many retinal images as the user requires, with their corresponding vessel networks, by sampling from a simple probability distribution that we impose to the associated latent space. We show that the learned latent space contains a well-defined semantic structure, implying that we can perform calculations in the space of retinal images, e.g., smoothly interpolating new data points between two retinal images. Visual and quantitative results demonstrate that the synthesized images are substantially different from those in the training set, while being also anatomically consistent and displaying a reasonable visual quality.

Description: Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

Description: The normalized differential spectral attenuation (NDSA) approach was proposed years ago as an effective way to estimate the integrated water vapor (IWV) along a tropospheric propagation path between two low Earth orbit satellites. Two applications are possible: the retrieval of vertical profiles of WV if the sense of rotation is opposite and the retrieval of 2-D fields of WV over vertical tropospheric sections if the sense is the same. The method relies on the measurement of the so-called spectral sensitivity $S$ at given frequencies, and on IWV-S relationships that convert $S$ into an estimate of IWV along the radio link where $S$ is measured. In this paper, we recompute the IWV-S relationships using synthetic atmospheres generated by means of European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data instead of radiosonde profiles as done by ourselves in the past. Thanks to the uniform spatial distribution of the ECMWF data on a global Earth scale, we were able to validate the IWV-S relationships in the Ku/K band previously found through synthetic atmospheres generated by means of the aforementioned irregularly spaced radiosonde data, and to define the IWV-S relationships at 179 and 181 GHz that are exploitable in the upper troposphere. Since the ECMWF data also include information about the liquid water (LW) content, we then show that an additional $S$ channel at 32 GHz can be exploited to detect and correct the bias induced by LW on IWV estimates made by applying the NDSA in the Ku/K band.

Description: This paper presents a compact planar tunable quadrature coupler with improved phase responses. Wide coupling-tuning ratio is achieved by using two varactors loaded on the center of the transmission lines of the modified coupler. Closed-form equations are derived for design parameters. For verification, a 1-GHz tunable coupler is designed and measured. The measured results agree well with the simulated ones. The measured power-dividing ratio can be tuned in a range from 16.2 to −35 dB (from 42 to 3.2E-4) with better than 20-dB return loss and isolation, while the phase imbalance is smaller than 10°. The coupler size is $0.21lambda text{g},,times ,,0.08lambda text{g}$ and reduced by 73.1% compared with the conventional branch-line coupler. The theoretical analysis shows that the phase imbalance and insertion loss are mostly caused by the loss from varactors. Then, a tunable coupler with improved phase and loss responses is proposed, where the additional phase difference and insertion loss resulting from the varactors are compensated for by introducing a negative resistance from the negative impedance converter. Measured results of a demonstrative 1-GHz coupler show a power-dividing ratio tuning range from 24.4 to −22.2 dB (from 275.4 to 6E-4) while maintaining 20-dB return loss and isolation. The phase imbalance is smaller than 1° and the insertion loss is improved by 1 dB and nearly close to theoretical values across the tuning range.

Description: This paper presents a new kind of highly flexible frequency-agile bandpass filters (FA-BPFs) based on the novel synchronously tuned dual-mode resonator (STDR). The bandwidth (BW), BW variation tendency, passband selectivity (stopband rejection level), and frequency tuning range of the filter can be predefined individually. Benefiting from the unique characteristics of the STDR, the FA-BPF with very simple and highly flexible design/control procedures is achieved. Due to the proposed geometry, two self-adaptive transmission zeros are introduced and move with the passband. The predefined mechanism is investigated in detail, and the simple design and predefined procedures are summarized. Then, three 0.75–1.7 GHz single-band examples with elliptic response are developed to achieve three predefined absolute BWs (ABW). The design techniques and filter superiority are confirmed by the experiments. Moreover, aiming at China 2G/3G/4G cellular wireless/mobile communication system (up to band 40:0.825–2.65 GHz), a novel intrinsically switchable single-/dual-band FA-BPF is presented based on the proposed STDR. An example with a constant ABW 1 dB and a fractional bandwidth 1 dB (FBW 1 dB is designed to validate the theory and analysis. The FA-BPF is able to operate as a highly selective dual-band FA-BPF with 0.76–1.78 GHz/1.61–2.63 GHz tuning ranges, and also can be switched to single-band operation with the continuous tuning range of 0.76–2.63 GHz.

Description: For the first time, the 6-port quadrature and rat-race couplers with balanced–unbalanced-hybrid ports are proposed. The corresponding design methodology is presented, which is capable of designing the proposed couplers with arbitrary power divisions and terminated resistances. In this paper, four types including quadrature and rat-race couplers are fully analyzed, covering all the application configurations of the balanced/unbalanced ports. Besides, the design equations are rigorously derived, with the final design procedures presented. Eventually, prototypes of the four coupler types are fabricated and experimentally measured. The final results sufficiently validate the proposed methodology.

Description: This paper presents the design and characterization of a load modulated balanced amplifier for telecom base station applications adopting a novel mode of operation. The theory of operation is described explaining the main differences compared to Doherty amplifiers, in particular the RF bandwidth advantages and, on the other hand, the intrinsic nonlinear behavior. The specific design strategy that adopts prematching for back-off broadband matching is explained in detail. A prototype, based on 25-W GaN packaged devices, has been fabricated and measured with single tone CW and modulated signal stimulus. For CW conditions, on the 1.7–2.5-GHz band, the peak output power is between 63 and 78 W, with power added efficiency higher than 48%, 43%, and 39% at saturation, 6- and 8-dB output power back-off, respectively. With a modulated signal for Long Term Evolution the amplifier provides an average output power of around 10 W, with efficiency higher than 40%, and can be linearized by adopting a low complexity predistorter. If compared to previously published power amplifiers targeting similar power and bandwidth, the measurement shows very good performance, demonstrating the potential of this novel technique in the field of efficiency enhanced transmitters.

Description: A new type of K-band high-Q frequency-tunable waveguide filters is proposed in this paper. The presented filter structure adopts a new technique for tuning the resonant frequency of each resonator. A dielectric plate is inserted in each resonator and rotating it leads to the frequency tuning. Unlike the conventional frequency tuning methodologies for tunable waveguide cavity filters, the new frequency tuning technique alleviates the electrical grounding issue for tuning devices. In addition, we demonstrate a new design method that allows the filter to have an absolute constant bandwidth in the frequency tuning range without using tunable coupling structures.

Description: Australia has likely the world's highest residential photovoltaic (PV) system penetration. In this paper, the impact of distributed PV on peak demand at different distribution network zone substations (ZSs) is assessed by upscaling 15 min PV generation data from 270 distributed PV systems across Sydney, Australia, and comparing it with load data from 138 ZS serving the Sydney region. Gross load (load had there been no PV) was estimated, allowing the impact of current and higher PV penetrations on the value and time of peak at the different ZSs to be assessed. A probabilistic assessment of the impact of PV on ZSs is conducted, based on the availability of PV during the peak demand periods. To better understand the impact of PV on peak demand, K-means clustering is used to group ZSs based on PV generation during peak periods as the clustering features. Mapping of PV availability across percentage of peak times for all ZSs highlights the interannual variability of peak reductions and the potential impact of short-term load shifting. The impact of different penetration levels of distributed PV on the peak demand of the entire distribution network is also assessed by aggregating the ZS loads.

Description: This paper reports on a broadband high-power amplifier (HPA) millimeter-wave integrated circuit (MMIC) covering the extended W-band (65–125 GHz). The MMIC is based on the Fraunhofer IAF 50-nm gate-length metamorphic high-electron-mobility transistor (mHEMT) technology. The HPA consists of two parallelized unit amplifiers. Each unit amplifier (UA) utilizes four stacked-HEMT unit power cells (UPCs) and four-way power combiners at the input and output. The UPCs stack four transistors with a gate width of $4times 40~mu text{m}$ per HEMT. The UA achieves an average small-signal gain of 19.4 dB and an average saturated output power of 21.6 dBm at least from 70 to 110 GHz. The HPA yields an average small-signal gain of 16.8 dB and an average saturated output power of 22.5 dBm at least from 68 to 110 GHz. A peak output power of 24.1 dBm is achieved at an operating frequency of 75 GHz.

Description: The general coupling matrix representation of bandpass filter (BPF) circuits is a widely used technique that has simplified the analysis and optimization of complex microwave filters. In this paper, we demonstrate a novel application of the general coupling matrix for modeling wireless power-transfer (WPT) systems based on the BPF model of magnetically coupled resonators. Compared to other methods of WPT analysis, our model simplifies accommodation of complex loads and provides direct expressions for impedance matching (IM) in WPT systems. Using this tool, we achieve optimal IM for two resonator systems with a complex load, thus achieving the greatest possible power-transfer efficiency (PTE). Furthermore, our model reveals additional design constraints for optimizing PTE in coupled resonator systems exhibiting low quality factor and small interresonator coupling. Overall, this paper introduces a new, versatile framework for the analysis and optimization of coupled resonator WPT systems. Experimental results are presented, verifying the optimal IM design process.

Description: In this paper, we present a new architecture for implementation of millimeter-wave (mm-wave) and terahertz (THz) radiator arrays based on standing-wave properties. This structure is a continuous distributed coherent array that avoids lossy and parasitic coupling networks. Moreover, it can be scaled simply by extending the size of the structure and replicating the unit cell. The absence of coupling parasitics in addition to the unique characteristics of standing waves allows us to extend the tuning range without using varactors. The 0.34-THz four-element radiator array is designed and fabricated in a 130-nm SiGe BiCMOS process using microstrip transmission lines as the standing-wave mediums and on-chip patch antennas to radiate the desired fourth harmonic of the oscillation. The circuit was measured with no post processing or silicon lens and has 5.9% frequency tuning range (332.5–352.8 GHz) with less than 6-dB output power variation across the band. It consumes 425-mW power from 1.8-V supply and the radiated power is −10.5 dBm at center frequency with −98.2 dBc/Hz phase noise at 10-MHz offset frequency.

Description: This paper presents an extension of synthetic aperture radar (SAR) techniques to enable simultaneous radar imaging, sensor tag localization, and backscatter-based data uplink from multiple sensor tags in a cluttered environment. A unified system model is presented that leverages coherent processing of backscattered signals gathered over the synthetic aperture for all three of these purposes. The proposed approach, using balanced orthogonal codes for SAR-based localization as well as the backscatter data uplink, is shown to have several favorable properties, including straightforward tag-vs-clutter discrimination, straightforward multiple access among tags, and improved signal-to-noise ratio during localization. A proof-of-principle indoor experiment is presented in the X-band (10–13 GHz) using two custom-designed backscatter tags interrogated by a vector network analyzer functioning as an FMCW radar. The proposed system model is validated by simultaneous imaging of a cluttered scene, tag localization with a maximum range error of 9 mm, and data demodulation from both tags telemetering temperature changes at a rate of 1 bit/s at ranges of 4.4 m and 4.7 m. The resulting point-spread functions of tags demonstrate a range resolution of 4.7 cm and a cross-range resolution of 9.1 cm.

Description: This paper proposes the application of information gap decision theory (IGDT) to the design of robust wide-area power system stabilizers (WPSSs) with consideration of wind farm (WF) power outputs variations and transmission line outages. According to IGDT, an optimization problem is constructed to tune WPSS parameters. Then, the derived optimal WPSSs can achieve explicit and favorable robustness to ensure the required damping control effects on the interarea oscillations over a maximum variation range of WF steady-state power outputs in normal and emergent operating conditions. Moreover, with the intent of using the excellent global searching capability of particle swarm optimization (PSO), a customized PSO algorithm is proposed to efficiently solve the resulting highly nonlinear programming problem. Finally, simulations are carried out on a modified New England (10-machine 39-bus) system to validate the efficiency of the IGDT-based design method. The derived WPSSs exhibit expected robustness with respect to the wind power variations and transmission line outages.

Description: The use of equivalent circuit models for simulating the operating behavior of lithium-ion batteries is well established in the automotive and the renewable energy sector. However, finding the correct parameter set for these models is still a challenging task. This manuscript proposes a comprehensive methodology for estimating the required, temperature dependent simulation parameters from battery measurements. Based on a specific load current and prior system knowledge, an algorithm first analyses the correlation between current steps and the measured terminal voltage. Second, a combination of particle swarm optimization and Gauss–Newton algorithm fits the initially estimated parameters from the first algorithm to the measurement data. Finally, the dependency of each simulation parameter on both the state of charge and the battery temperature is determined. As this contribution aims at modeling reversible effects of lithium-ion batteries, ageing effects are neglected. The validation against measurement data proves that the generated parameter set enables the user to accurately reproduce and investigate the operating behavior of the chosen battery. Applied to a lithium-iron-phosphate cell, the comparison between measurements and simulations in standardized real-life automotive driving cycles (Artemis, FTP75 and WLTC) shows a terminal voltage error of less than 1.09% within the typical operational window between state of charge 0.15 and 0.95.

Description: In this paper, a scalable wide area control scheme using distributed model predictive control is proposed to enhance the angle stability of power systems following large disturbances. In this regard, dynamic model of the local subsystems in the multiarea power system is developed for the model predictive controller and each subsystem is controlled by the associated controller. The controller of each subsystem exchanges minimum information with the controllers of the neighboring subsystems to reach the final result. The proposed controller works based on optimality condition decomposition to coordinate the subsystems. In the proposed wide area control system, the available actuators are mechanical power and field voltage controller of a synchronous generator, and energy storage systems (ESS), which are able to provide synchronizing power support. The performance of the proposed transient stability controller is studied in the New England 68-bus test system. The simulation results demonstrate the effectiveness of the proposed method to improve the angle stability of power systems subsequent to severe disturbances in the system.

Description: In this paper, an adaptive multiobjective fractional-order fuzzy proportional–integral–derivative controller is proposed for the load frequency control (LFC) of islanded microgrids (MGs), while benefiting from the assets of electric vehicles (EVs) in this respect. Although the use of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources, a new multiobjective fractional-order control strategy for the EVs in V2G scenarios is proposed in this paper. Moreover, since the performance of the controller depends on its parameters, optimization of these parameters can play a significant role in promoting the output performance of the LFC control; hence, a modified black hole optimization algorithm is utilized for the adaptive tuning of the noninteger fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop simulations are presented to prove that the proposed controller tracks frequency with lower deviation and fluctuation and is more robust in comparison with the prior-art controllers used in all the case studies.

Description: We develop a decision-making tool based on a bilevel complementarity model for a merchant price-maker energy storage system to determine the most beneficial trading actions in pool-based markets, including day-ahead (as joint energy and reserve markets) and balancing settlements. The uncertainty of net load deviation in real-time is incorporated into the model using a set of scenarios generated from the available forecast in the day-ahead. The objective of this energy storage system is to maximize its expected profit. The day-ahead products of energy storage system include energy as well as reserve commitment (as one of the ancillary services), whereas its balancing product is the energy deployed from the committed reserve. The proposed model captures the interactions of different markets and their impacts on the functioning of the storage system. It also provides an insight for storage system into clearing process of multiple markets and enables such a facility to possibly affect the outcomes of those markets to its own benefit through strategic price and quantity offers. The validity of the proposed approach is evaluated using a numerical study.

Description: This paper focuses on the enhanced control and improved fault-ride-through capability of a doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) under disturbed grid conditions. An adaptive sliding-mode control of stator powers, with sensorless rotor current and constant switching frequency, is introduced. The proposed control method is derived directly from the nonlinear DFIG state model, and the control law is computed based on nominal stator flux. Therefore, the flux estimation or measure, which is cumbersome in some methods, is no longer required. Furthermore, an adaptive term is added to sliding-mode control in order to attenuate the chattering effect. The proposed control law is validated via simulations in the case of 1.5 MW DFIG-based WECS, and experimental results on a 7.5 kW hardware prototype. The control system robustness and performance is assessed in the presence of modeling errors, parameter variations, and grid side disturbances, such as voltage dip, swell, imbalance, distortion, and flicker (according to IEEE Standard 1159).

Description: The presence of uncertain parameters in design of microgrids (MG) adds significant challenges for MGs planner when it comes to making decisions. To address the uncertainties in the technical and pecuniary information especially in the case of lack of full information on the nature of uncertainty, this paper proposes a novel robust optimization approach for optimum design of MGs considering reconfigurable topology. The proposed approach investigates the economic and reliable structure for MGs deployment and optimal planning of distributed energy resources with section switch and tie switch (TSW) allocation to determine MGs boundaries and topologies. The optimal TSW allocation is implemented in order to change the configuration of distribution network to increase robustness of MGs versus uncertainty. The profit-based objective function is converted into robust framework and, subsequently, has been transformed into single level model by duality gap theory. Finally, grey wolf optimization algorithm has been carried out to solve the proposed model. The appraisement of the proposed model is accomplished by applying it on the IEEE 30-bus distribution system and results of case study demonstrate the effectiveness of the proposed method.

Description: This paper presents a multistage stochastic programming formulation of a transmission-constrained economic dispatch subject to multiarea renewable production uncertainty, with a focus on optimizing the dispatch of storage in real-time operations. This problem is resolved using stochastic dual dynamic programming. The applicability of the proposed approach is demonstrated on a realistic case study of the German power system calibrated against the solar and wind power integration levels of 2013–2014, with a 24-h horizon and 15-min time step. The value of the stochastic solution relative to the cost of a deterministic policy amounts to 1.1%, while the value of perfect foresight relative to the cost of the stochastic programming policy amounts to 0.8%. The relative performance of various alternative real-time dispatch policies is analyzed, and the sensitivity of the results is explored.

Description: With increasing penetration of wind power, it is recognized that manufacturer-specific models of wind turbines are not appropriate for power system studies, and the equivalent model of wind farms required by dynamic modeling poses a complicated technical challenge. In this paper, a practical equivalent method for wind farms with doubly fed induction generator (DFIG) wind turbines is proposed. Three critical steps are involved in this method. Step 1, modeling of a wind turbine, the model incorporating the complete fault ride through process is constructed and validated for an operational DFIG wind turbine. Step 2, clustering of wind turbines, a practical four-machine equivalent method is proposed. Initially, dynamic responses of active power of a DFIG wind turbine operating at various wind speeds are investigated to obtain three clusters of wind turbines, then four clusters are further determined by improving equivalency error at some typical wind speed scenarios. Step 3, an analytical method is proposed to determine the equivalent collector network parameters for each of the four equivalent machines. The proposed method is validated by comparing with the single-machine representation and the detailed wind farm model. Simulation results show that the proposed method has good performance for different fault durations, voltage dips, and changing wind scenarios.

Description: A new method for the control of a battery energy storage system and its implementation on a 25 kW solar system to compensate solar power intermittency and improve distribution grid power quality is presented in this paper. The novelty of the proposed method is to provide a systematic way to optimize the size of the battery capacity for the desired level of solar power smoothing. This goal is achieved by designing a two-stage filter solution. The first stage is a fast response digital finite impulse response (FIR) filter that makes a trade-off between smoothing of the solar output and battery capacity. This paper proposes an optimal design of a minimum-length, low-group-delay FIR filter by employing convex optimization, discrete signal processing, and polynomial stabilization techniques. The new strategy proposed in this paper formulates the design of a length- $N$ low-group-delay FIR filter as a convex second-order cone programming, which guarantees that all the filter zeros are inside the unit circle (minimum-phase). A quasi-convex optimization problem is formulated to minimize the length of the low-group-delay FIR filter. The second-stage filter is designed to level the battery charging load. The effectiveness and performance of the proposed approach is demonstrated by simulation results and also over a real-case implementation.

Description: Gas-fired generation provides flexibility to the power system for peak-load shaving and reserve allocation. Large penetration of renewables strengthens the gas-electric coupling. Consequently, constraints to the operations of the high-pressure gas transmission system may endanger the security of power supply. To address this issue, we assess the impact of gas constraints on the day-ahead electric power and reserve scheduling. Furthermore, we investigate the effect of unforeseen, large negative ramps of wind power generation on the gas network operations. The day-ahead scheduling of electric generator dispatch and reserves is determined via a stochastic, N-1 secure optimization. Minimum-pressure constraints update the scheduling of electric generators and reserves. The simplified energy infrastructure of Great Britain in the 2030 Gone Green scenario is investigated for diverse gas load and wind availability conditions. Results show that large gas demands decrease linepack and cause gas-fired units to shut down due to minimum pressure violations. In scarce-wind conditions, gas network limitations largely affect reserve scheduling and nonelectric gas curtailments are needed to comply with pressure safety margins. Conversely, reserve planning including gas constraints prevents pressure violations caused by unexpected wind fluctuations. These results support operators and regulators by providing a technoeconomical evaluation of the gas-electric interdependencies.

Description: This paper emphasizes the development of a simplified active power control scheme for enhanced operation of grid integrated permanent magnet synchronous generator based wind-driven generators (WGs). An active power reference generation scheme is proposed for the machine side converter (MSC) to inject active power into the grid even under grid disturbances, without violating system components rating. In this scheme, the controller employed for MSC adjusts the active power captured proportionate to the drop in the grid voltage upon considering wind speed and rotor speed. Furthermore, unlike dual vector control scheme, the grid side converter controller is implemented in a positive synchronous frame with the proposed current oscillation cancellation scheme to suppress the oscillations in dc-link voltage, active and reactive power of the grid and to obtain symmetrical sinusoidal grid current. Extensive analytical simulation has been carried out in PSCAD/ EMTDC to validate the superiority of proposed control scheme over the conventional schemes when WG is subjected to various grid disturbances. The reduced percentage of oscillation in the system parameters such as dc-link voltage and grid active power confirms the efficacy of the proposed method when compared with the conventional control techniques.

Description: A two-stage, high-power symmetric Doherty power amplifier (PA) at 15 GHz is presented. The PA is implemented in 45 nm CMOS silicon on insulator and achieves more than 23 dB power gain with 25.7 dBm saturated output power and 31% peak power added efficiency (PAE). The 6 dB back-off PAE is 25%, which is a 64% improvement compared to ideal class B PA back-off performance. High output power is obtained by employing four-stack multigate devices at the output stage; driver stages employ two-stack devices. A simple analog predistortion linearizer is proposed that effectively corrects the AM–AM response of the Doherty PA and extends the P1dB from 23 to 25.1 dBm. The PA also exhibits excellent AM–PM response. The amplifier has compact dimensions and occupies only 1 mm 2 chip area, including pads.

Description: This paper presents a method to achieve optimal active and reactive power contributions from each energy storage system in an unbalanced distribution network to minimize power loss, while ensuring network current and voltage constraints are satisfied. By modeling loads as either constant current or constant impedance, the ac optimal power flow is transformed into a noniterative convex optimization problem. The application of capacity constraints, voltage constraints, and energy storage constraints in an unbalanced three-phase four-wire system is considered, addressing specific issues pertaining to unbalanced networks such as voltage unbalance and neutral voltage displacement. The proposed method is then used to demonstrate optimized dispatch of energy storage systems in a suitable four-wire unbalanced distribution test network. The contribution of losses in the neutral wire to the total losses is also determined for a test system under a range of operating conditions and various neutral earthing systems, highlighting the importance of considering this in a typical unbalanced distribution network.

Description: In this paper, a novel design theory of two-section two-resistor Wilkinson power divider (WPD) is introduced. By selecting two different physical lengths of two-section transmission lines (TLs), two arbitrary frequency band WPD can be achieved. Compared with the former work, the designable frequency ratio range $u$ can be extremely extended from $1 〈 u 〈 3$ to $1 〈 u 〈 infty$ , general design equations for characteristic impedances, physical lengths, absorption resistors, and frequency ratio ranges are newly derived and proved from even- and odd-mode analysis. Because of no capacitors or inductors, the proposed WPD can be used for high-frequency applications. Spurious band of $S_{21}$ appears between two passbands under the condition of two different physical lengths; therefore, a $Pi$ -type dual-band transformer is newly introduced to replace single TL for spurious band suppression. We proved that $Pi$ -type structure could effectively suppress spurious band of $S_{11}$ , maintain two arbitrary frequency passband of $S_{21}$ , and provide an extra isolation band of $S_{32}$ at center frequency. Finally, three proposed WPD examples with $Pi$ -type structure are selected with diffe- ent frequency ratios, where frequency ratio $u = 4$ in Example A, $u = 6$ in Example B, and $u = 20$ in Example C are designed and fabricated in the experiment. Measured results show good agreement with the theoretical results.

Description: In this paper, a technique to extend the linearity and to improve the efficiency of power amplifiers (PAs) is analyzed. The method avoids complex topologies, often affecting the radio-frequency performance and increasing the power consumption, chip area, and costs. In contrast, this approach can be implemented by a simple, but sophisticated design of the input biasing network. In this case, the input biasing network works in such a way that the dc current consumption adapts inherently to the demanded output power while ensuring high linearity. The large-signal behavior is analyzed, and analytical equations for the optimum parameter of the bias network are derived. For integration reason, the network is extended to a compact solution, which also includes the source resistance. According to these theoretical considerations, a PA is implemented in a 0.25- $ {mu }text{m}$ SiGe BiCMOS process. The analytical solutions are verified by the measured output-referred 1-dB compression point of 23.6 dBm. To estimate the improvement by using optimum values of the elements, simulations reveal an increase of the input-referred compression point by 2 dB and by 7% of power-added efficiency.

Description: In this paper, a receiver architecture is presented which is capable of handling angle-of-arrival (AOA) detection as well as data communication. The architecture of the proposed multifunction receiver is based on the multiport interferometer technique, and it integrates two previously reported six-port-based system functions that were realized as two distinct six-port receivers (SPRs). This unification of two SPRs is mainly achieved through a new configuration of RF/local oscillator (LO) signals at input ports, a new phase processing of the input signals within a structured eight-port passive network and a complementary postprocessing of the signals at the output of detectors. Using two RF input ports and two LO input ports that are switched in two consecutive time slots, the proposed multiport-based receiver (MPR) can estimate the AOA with a simple signal-processing algorithm. The plurality of the RF input ports can cause self-interference for the received communication signals. Therefore, a phasing network within the proposed eight-port wave correlator is devised such that the incoming quadrature modulated RF carriers are demodulated in an orthogonal manner at four output ports. It is found that receiving communication signal from a nonzero AOA makes imbalance between demodulated components. To this end, the proposed MPR can first find the angular position of the other unit and then recover the demodulation components through data fusion and postprocessing. The mathematical model for the developed MPR is derived along with the development of an appropriate calibration technique, and its principal functionality is theoretically analyzed. In addition, a transceiver architecture based on this MPR is implemented, and prototyped for operation around 77 GHz. The techniques for hybrid millimeter-wave system integration are explained in this paper. The proposed concept is proven and concluded with satisfactory measurements for both functions. This unified multifunction M- R can find applications in the future vehicle-to-vehicle radios and joint radar-communication systems.

Description: The transmitter (TX)-induced interference due to power amplifier nonlinearities poses severe desensitization problems to the receiver chain in frequency-division duplexing transceivers. Due to nonlinear signal process involved, a high sampling rate is normally required in the existing digital suppression approaches, which can result in high cost and high power consumption in wideband systems. In this paper, a new digital suppression model is proposed to cancel the TX leakage at baseband with a low sampling rate. The cancellation model is based on the modified decomposed vector rotation model. With the addition of cross-term products, the enhanced model is capable of eliminating the aliasing effect arising from the reduced sampling rate. Theoretical analysis of aliasing elimination is presented, and the algorithm is subsequently verified by both simulation and experiment results, confirming the effectiveness and feasibility of the proposed cancellation technique for TX leakage suppression. Compared with conventional solutions, the new approach uses much less hardware resource and consumes much lower power while achieving comparable performance.

Description: In this paper, we propose an experimental approach for determining the internal electric field for exposure evaluation of wireless power transfer (WPT) systems by using measured magnetic near-field data. Two WPT systems are fabricated and used in the measurements: one without ferrite tiles, and the other with ferrite tiles and a metal plate. The amplitude and phase of the magnetic near field in the vicinity of the WPT systems are then measured by using in-house magnetic-field probes and a near-field measurement system. Numerical dosimetry of human exposure is performed using the measured near field as an incident field in the impedance method to derive the internal electric field strength inside numerical human models. Validation of the proposed approach has been demonstrated by comparing measurement results with those obtained from numerical simulations. Additionally, the coupling factor, which represents the relationship between the incident magnetic field and the induced electric field in the human body, at different distances is derived for realistic exposure scenarios.

Description: In this paper, a new method to design a digitally assisted and spurious-free direct carrier mixerless modulator based on the six-port correlator is proposed. The calibration of the modulator based on modified Cartesian memory polynomial (MCMP) is used to linearize and mitigate hardware impairment of the whole system. The modulation and the up conversion are performed by using the variable loads controlled by the differential in-phase and quadrature-phase baseband voltages together with common-mode voltages. The proposed MCMP is able to compensate for nonlinearity, frequency responses, residual carrier leakage, crosstalk between the in-phase and the quadrature-phase data. The proof-of-concept of digitally assisted mixerless modulator is developed and its performance is assessed at 2.6 GHz with modern communication signals. The error vector magnitudes between the input ideal baseband signals and the up-converted radio frequency signals are all between 2% and 4%. The residual carrier leakage, which remains present after imperfect suppression through hardware means, degrades the overall system performance and it can be suppressed completely by means of the proposed memory polynomial model.

Description: Real-time spectrum sensing refers to searching for possible signals at a specific time and location, which is applicable to cognitive radio for primary signal detection. The simplicity and low sensing time of phaser-based spectrum sensors, implemented in a discrete manner previously, provided the incentive for this paper. In this paper, an integrated CMOS wideband real-time spectrum sensor with a novel on-chip phaser in 57–354-MHz band, as part of VHF/UHF TV broadcast bands, is presented. The proposed approach provides a fast, simple, area-efficient analog solution for real-time spectrum sensing with low noise figure and power consumption. The integrated chip has been fabricated in a standard 0.18- $mu text{m}$ CMOS IBM technology and has achieved a sensing time of as low as 2.5 $mu text{s}$ for 27-MHz frequency resolution.

Description: This paper presents an adaptive droop-based power-sharing control strategy. The primary objective is to control the sharing of the active power transmitted by a multiterminal voltage-source converter based high voltage direct current network among a number of onshore ac grids or offshore loads based on the desired percentage shares. The shared power is generated by remote generation plants (e.g., offshore wind farms) or is provided as surplus from ac grids. The desired percentage shares of active power are optimized by the system operator in order to fulfil the active power requirements of the connected grids with respect to meeting goals such as supporting energy adequacy, increasing renewable energy penetration, and minimizing losses. The control strategy is based on two hierarchal levels: voltage-droop control as the primary controller and an optimal-power flow based secondary (supervisory) controller for selecting the optimal droop reference voltages. Based on the dc voltage transient and steady-state dynamics, a methodology for choosing the droop gains for droop controlled converters has been developed. The proposed control strategy has been validated through simulation on the CIGRE B4 dc grid test system. The results confirmed the flexibility and effectiveness of the power-sharing control provided by the new control strategy.

Description: This paper presents a new nonlinear current control strategy based on backstepping control and high-order sliding mode differentiator in order to employ distributed generation (DG) unit interfacing converters to actively compensate harmonics/interharmonics of local loads. The converter-based DG unit is connected to a weak grid (with uncertain impedance) and local load (that can be parametrically uncertain and topologically unknown) through an LCL filter. The proposed strategy robustly regulates the inverter output currents and delivers pure sinusoidal, three-phase balanced currents to the grid. The new controller demonstrates the robust performance and robust stability of the DG unit system with respect to the filter parameters uncertainties, grid impedance, grid frequency, and grid voltage as well as the unknown load dynamics that include unbalanced loads and nonlinear loads with harmonic and interharmonic currents. We should remark that the local compensation of the loads with interharmonic current using a DG unit system is first proposed in this paper. When compared with the popular parallel proportional resonant control technique, the proposed controller offers smoother transient responses and a lower level of current distortion. The performance of the proposed control strategy is verified in MATLAB/SimPowerSystems toolbox.

Description: Optimally dispatching photovoltaic (PV) inverters is an efficient way to avoid overvoltage in active distribution networks, which may occur in the case of the PV generation surplus load demand. Typically, the dispatching optimization objective is to identify critical PV inverters that have the most significant impact on the network voltage level. Following, it ensures the optimal set-points of both active power and reactive power for the selected inverters, guaranteeing the entire system operating constraints (e.g., the network voltage magnitude) within reasonable ranges. However, the intermittent nature of solar PV energy may affect the selection of the critical PV inverters and also the final optimal objective value. In order to address this issue, a two-stage robust centralized-optimal dispatch model is proposed in this paper to achieve a robust PV inverter dispatch solution considering the PV output uncertainties. In addition, the conic relaxation-based branch flow formulation and the column-and-constraint generation algorithm are employed to deal with the proposed robust optimization model. Case studies on a 33-bus distribution network and comparisons with the deterministic optimization approach have demonstrated the effectiveness of the proposed method.

Description: The dynamic economic dispatching of power system connected with multiple wind farms is a typical stochastic programming problem. How to model the randomness of wind power and how to solve this complex stochastic optimization problem are the key points. In this paper, copula theory is used to formulate the correlation of multiwind farms generation. Then, the dynamic economic dispatching model is founded with the fuel consumption, gas pollution emission fees, and electricity purchase costs as the optimized objective. The two-stage compensation algorithm is then introduced to solve the dispatching problem. In this algorithm, the conventional (nonstochastic) decision variables and stochastic variables are decoupled, which separate the dynamic dispatching model into two stage modes. The optimal dispatching result is worked out by iteration between the two stage models. Case studies on IEEE118-bus system and an actual provincial power grid show that the proposed algorithm can drastically reduce computational burden, and satisfy the actual requirements of engineering practice.

Description: A single-stage flyback PV inverter with maximum power point tracking (MPPT) high-speed capability is presented in this paper. The proposed stand-alone photovoltaic energy system (SAPES) incorporates the use of hybrid MPPT to ensure peak energy harvesting under all weather conditions. The proposed hybrid MPPT method combines the conventional short current pulse (SCP) MPPT method and the perturb and observe (P&O) methods. Measurement of the offline parameter [short-circuit current of PV module ( ${I}_{rm sc}$ )] for SCP is made on the basis of the difference between the offline parameter and the instantaneous current of PV module ( ${I}_{rm pv}$ ). Use of a single power conversion stage is achieved by employing a modified flyback inverter operating in a discontinuous-conduction mode. The control structure of the conventional flyback inverter is also modified to incorporate the hybrid MPPT algorithm. The proposed SAPES method is tested using computer-aided simulations and real-time hardware in the loop experimentation using the dSPACE DS1104 board. The results obtained using the proposed systems are better than those for the conventional algorithms under the environmental conditions tested.

Description: The large-scale integration of a grid-scale energy storage and the increasing penetration of renewable resources motivate the development of techniques for determining the optimal ratings and locations of storage devices. This paper proposes a method for identifying the sites where energy storage systems should be located to perform spatio-temporal energy arbitrage most effectively and the optimal size of these systems. This method takes a centralized perspective where the objective is to minimize the sum of the expected operating cost and the investment cost of energy storage. It has been tested on a realistic 240-bus 448-line model of the Western Electricity Coordinating Council (WECC) interconnection. The influence on the results of the following parameters is analyzed: Maximum number of storage locations, maximum size of storage systems, capital cost of deploying storage, value assigned to spillage of renewable energy, marginal cost of conventional generation, and renewable generation capacity. These numerical results are used to characterize the benefits that energy storage can provide in prospective large-scale power systems with renewable generation.

Description: In this study, we propose a novel distributed secondary control scheme for both voltage and frequency in autonomous microgrids. By incorporating predictive mechanisms into distributed generations, the secondary voltage control is converted to a tracker consensus problem of distributed model predictive control, with the synchronous convergence procedure for voltage magnitudes to the reference value drastically accelerated at a low communication cost. A sufficient local stability condition with the parameter analysis is established. Thus, a distributed proportional integral method combined with a finite-time observer to estimate the global reference information is presented in the frequency restoration while maintaining accurate active power sharing. Our approach accommodates model uncertainty, plug-and-play capability, and especially robustness against information update intervals, which is essential when the conventional method probably yields toward a poor performance. Meanwhile, the distributed architecture implemented on the local and neighboring information allows for a sparse communication network and eliminates the requirement for a centralized controller. Simulation results are provided to verify the effectiveness of the proposed control methodology.

Description: This paper proposes an $mathrm{H}_{infty}$ robust current controller for doubly-fed induction-generator (DFIG)-based wind turbines subject to grid voltage distortions. The controller is to mitigate the impact of the grid voltage distortions on rotor currents with DFIG parameter perturbation. The grid voltage distortions considered include asymmetric voltage dips and grid background harmonics. An uncertain DFIG model is developed with uncertain factors originating from distorted stator voltage, and changed generator parameters due to the flux saturation effect, the skin effect, etc. Weighting functions are designed to efficiently track the unbalanced current components and the fifth and seventh background harmonics. The robust stability and robust performance of the proposed controller are verified by the structured singular value μ. The performance of the $mathrm{H}_{infty}$ robust current controller was demonstrated with a 1.5-MW DFIG model, showing its harmonics suppression ability with DFIG parameter perturbation and improved robustness.

Description: This paper presents a comprehensive sensitivity analysis to identify the uncertain parameters which significantly influence the decision-making process in distributed generation (DG) investments and quantify their degree of influence. To perform the analysis, a DG investment planning model is formulated as a novel multistage and multiscenario optimization problem. Moreover, to ensure tractability and make use of exact solution methods, the entire problem is kept as a mixed-integer linear programming optimization. A real-world distribution network system is used to carry out the analysis. The results of the analysis generally show that uncertainty as well as operational variability of the considered parameters have meaningful impacts on investment decisions of DG. The degree of influence varies from one parameter to another. But, in general, ignoring or inadequately considering uncertainty and variability in model parameters has a quantifiable cost. Hence, the analysis made in this paper can be very useful to identify the most relevant model parameters that need special attention in planning practices.

Description: Hyperspectral image classification has been a vibrant area of research in recent years. Given a set of observations, i.e., pixel vectors in a hyperspectral image, classification approaches try to allocate a unique label to each pixel vector. However, the classification of hyperspectral images is a challenging task for a number of reasons, such as the presence of redundant features, the imbalance among the limited number of available training samples, and the high dimensionality of the data.

Description: Land-cover mapping in remote sensing (RS) applications renders rich information for decision support and environmental monitoring systems. The derivation of such information increasingly relies on robust classification methods for identifying the complex land-cover area of different categories. Numerous classification techniques have been designed for the analysis of RS imagery. In this context, support vector machines (SVMs) have recently received increasing interest. However, the need for a small-size training set remains a bottleneck to design efficient supervised classifiers, while an adequate number of unlabeled data is readily available in RS images and can be exploited as a supplementary source of information. To fully leverage these precious unlabeled data, a number of promising advanced SVM-based methods, such as active SVMs, semisupervised SVMs (S3VMs), and SVMs combined with other algorithms, have been developed to analyze satellite imagery. In this literature review, we have surveyed these learning techniques to explore RS images. Moreover, we have provided the empirical evidences of SVMs and three representative techniques. It is our hope that this review will provide guidelines to future researchers to enhance further algorithmic developments in RS applications.

Description: Since 2006, the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) organizes a yearly Data Fusion Contest that aims to promote the use of new remote sensing data sources and stimulating new methodological developments [1]-[10].

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Description: In this letter, we focus on stub resonators embedded in plasmonic slot waveguides. The resonators have potential applications in optical interconnects and sensors. We fabricate the samples by electron beam lithography and lift-off. We use a scattering matrix-based model to quantify the optical power output from the samples. We measure the properties of the resonators by coupling light in and out of the slot waveguides by optical antennas, making use of a cross-polarization-based setup utilizing a supercontinuum source and a high numerical aperture objective lens operating in the telecom-wavelength range. Our model agrees well with the measured data. Furthermore, development on the stub resonators can be made by using the methods in this letter.

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Description: The use of a fixed forward power as obtained during the calibration phase in a bulk current injection test, without monitoring the current, may cause damage on the equipment under test (EUT) with low impedances. In this paper, an accurate EUT model has been designed based on impedance investigation. This model can be used to predict the conducted susceptibility of a generic EUT. The model is first based on black-box approach; then, an interaction model is added to provide flexibility of several geometric parameters, which can be changed from one setup to another. This methodology leads to the combined approach, which shows a satisfactory agreement between simulations and measurements. According to the developed equations, the impedance matrix of the described model can be readily switched to modal one. Afterward, asymmetric dummy EUTs were investigated and the analytical equations used to predict differential mode due to common-mode voltage injection were validated.

Description: In this paper, we analyze the impact of characteristic impedance variations among standards on the accuracy of the thru-reflect-line (TRL) calibration technique. The impedance transformer method is adopted to derive the expressions of the calibration coefficient errors due to the manufacturing tolerances. It is found that three factors can affect the magnitude of the errors in the calibration coefficients (c/a and b terms), which are crucial to get the final calibrated results. The first factor is related to the original parameters of the error networks (test fixtures): the larger the insertion losses, the smaller the error in b ; the error in c/a may see an opposite trend if the error network is lossy instead of lossless. The second factor is denoted as the phase contribution (one of the three multipliers of the derived error expression): the magnitude of this error contributing item is approximately equal to the ratio of two hyperbolic sine functions, the variables of which are the length of Line and the length difference between Line and Thru, respectively. The third factor comes from the impedance differences between Thru and Line: the smaller the impedance variation, the smaller the error. The error analysis, presented here, can help engineers evaluate the calibration accuracy by analyzing the error contributing items. It also can be further used to guide test fixture designs to maximize TRL's error immunity to the transmission line characteristic impedance variations.

Description: This paper evaluates several techniques capable of mitigating the impact of low-power radio frequency jammers that interfere with ground-to-train communications. These radio communications are used for railway signaling, and interfering with these signals can have a negative impact on the train operation. Although the commercialization, detention, and use of radiofrequency jammers is strictly forbidden in most countries, they can be easily found on the internet at low cost and unexpectedly switched on by a passenger in a moving train. In this paper, we evaluate and compare the ground-to-train radio communication and intentional electromagnetic interference (IEMI) received signal powers delivered by roof train antennas to the train control command receiver. This comparison is used to deduce the potential zones of interference along the train trajectory and its consequences. Operating at the physical layer, we then propose and evaluate three mitigations techniques that can be used separately or combined to reduce the impact of this type of interference. We show that they can significantly reduce the jamming capability and help us in maintaining railway full operation.

Description: The evaluation of the ground admittance of an underground insulated conductor with a homogeneous nonmagnetic earth is of great significance when the electromagnetic compatibility is concerned. To evaluate the ground admittance efficiently, researchers proposed that the ground impedance of the conductor should be evaluated first and the ground admittance is related to the ground impedance through the wave number in the soil. There are several approximated analytical expressions for the evaluation of the ground impedance with a homogeneous earth and this fact makes the ground admittance easy to obtain. The characteristic of the approximated ground admittance evaluation approach is examined in this paper. Numerical examples illustrate that at frequencies with which the burial depth is much larger than the skin depth in the soil, the ground admittance and the ground impedance of the buried cable are well-related through the wave number in the soil. However, at other frequencies, the approximated approach fails to evaluate the ground admittance accurately. This paper also reveals that the discrepancy of the ground admittance will lead to a noticeable difference in the lightning induced voltage on buried cables.

Description: Cascade application of surge protective devices (SPDs) in low-voltage ac power circuits is intended to ensure proper equipment protection against surges as well as to provide surge energy distribution between SPDs. In order to evaluate equipment response and SPDs performance, concept of representative surges, which can be used for surge testing purposes, is introduced by international standards. Combination wave surge is defined both by IEEE C62.41.2 standard and IEC 61000-4-5 standard as one of the representative surges. However, these standards specify different tolerances regarding short-circuit current waveform's undershoot delivered by combination wave generator (CWG). The aim of this paper is to investigate the influences of different CWGs regarding short-circuit current undershoot in cascade two-stage protection system. It will be shown that differences that appear during surge testing with application of different CWGs can lead to inappropriate selection of SPDs regarding energy absorption capability and/or protection level.