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In this paper, a pervasive wireless channel modeling theory is first proposed, which uses a unified channel modeling method and a unified equation of channel impulse response (CIR), and can integrate important channel characteristics at different frequency bands and scenarios. Then, we apply the proposed theory to a three dimensional (3D) space-time-frequency (STF) non-stationary geometry-based stochastic model (GBSM) for the sixth generation (6G) wireless communication systems. The proposed 6G pervasive channel model (6GPCM) can characterize statistical properties of channels at all frequency bands from sub-6 GHz to visible light communication (VLC) bands and all scenarios such as unmanned aerial vehicle (UAV), maritime, (ultra-)massive multiple-input multiple-output (MIMO), reconfigurable intelligent surface (RIS), and industry Internet of things (IIoT) scenarios. By adjusting channel model parameters, the 6GPCM can be reduced to various simplified channel models for specific frequency bands and scenarios. Also, it includes standard fifth generation (5G) channel models as special cases. In addition, key statistical properties of the proposed 6GPCM are derived, simulated, and verified by various channel measurement results, which clearly demonstrates its accuracy, pervasiveness, and applicability. [ABSTRACT FROM AUTHOR]

Harmonics generated from power electronic converters will impose significant power quality challenges to the electric grid onboard future aircraft. In this article, we propose an innovative modulation scheme that enables using a buck–boost dc–dc converter as a harmonic absorber. To demonstrate the effectiveness of the proposed method, a hybrid power generation system involving a high-speed electrical generator and a high voltage battery is introduced. The electrical generator is connected to a dc bus through an ac–dc converter and the battery to the dc bus with a dc–dc converter. For the studied hybrid power generation system, it is identified that the first carrier frequency side-band harmonic (fc-3f0) from the ac–dc converter is most relevant and is targeted for cancellation. For the control of the dc–dc converter, a new modulation technique, called equal-gate-width modulation is proposed. It allows active control of the magnitude and phase angle of some specific harmonic components from a dc–dc converter. By properly tuning the phase angle and amplitude, the controlled harmonics can thus be used to cancel harmonics from other converters on a common dc bus. Without losing generality, this article focuses on the development of this specific harmonic cancellation scheme and the effectiveness of our proposed methods has been demonstrated using experimental results. [ABSTRACT FROM AUTHOR]

In this work, a new type of graphene ICs only comprising multiple graphene field-effect transistor (GFET) components is first reported. Based on the GFET design that enables homogeneous electrical characteristics in batch-made devices, the practicality and functionality significances of multi-GFET integration are experimentally demonstrated via high-fidelity amplifiers for baseband analog signals. Different from the quadratic relationship of the gate-controlled current output (in saturation region) in the traditional silicon-based MOSFETs, the saturation current output of GFETs relating to the gate-controls possesses high linearity. This advantage overcomes the inherent nonlinear distortion issues in the existing silicon MOSFET amplifiers and potentially provides a promising scenario for the accurate preamplification of weak analog signals. Besides, the novel circuit configuration and signaling principle may expand the developmental paradigm of analog amplifiers and set groundwork for the development and practicalization of advanced carbon-based nanoelectronic ICs. [ABSTRACT FROM AUTHOR]

This article proposed a harmonic suppression scheme that used a dc-dc converter as an active harmonic injector to cancel voltage harmonics on the HVdc bus within a hybrid power generation centre (HPGC). A permanent magnet synchronous generator and a battery are considered to supply power to a common HVdc bus through their dedicated ac-dc and dc-dc converters respectively within the HPGC. We proposed simplified mathematical models of harmonics from the ac-dc and dc-dc converters. Thereafter, an active power sharing scheme between the PMSG and the battery is developed to control the magnitudes of targeted harmonics to be the same. The targeted harmonics on the HVdc bus can thus be cancelled by properly tuning the carrier signal phase angles within ac-dc and dc-dc converters. A closed-loop control scheme has been developed and this scheme is with no extra hardware cost. To demonstrate the effectiveness of the proposed scheme, we selected the first-band harmonic (fc − 3f0) as the targeted harmonic component. The harmonic cancellation scheme for this component has been developed and validated using experimental results. It has been demonstrated that the proposed method can achieve over 90% reduction of this specific harmonic component on the HVdc bus within this HPGC using one dc-dc converter. [ABSTRACT FROM AUTHOR]

In this paper, a novel 3-dimensional (3D) non-stationary geometry-based stochastic model (GBSM) is proposed to mimic the ship-to-ship multiple-input multiple-output (MIMO) communication channels. To reflect the realistic maritime propagation environment, the effects of rough sea surface scattering and evaporation duct propagation are investigated in the proposed channel model. The model considers the movements of transmitter (Tx), receiver (Rx), and scatterers, and is capable of capturing the channel characteristics, including non-stationary characteristics, spatial consistency, location-dependent property, etc. Through taking the array cluster evolution into account, the proposed channel model can describe massive MIMO channels and can easily switch to conventional MIMO channel model by adjusting corresponding parameters. Based on the proposed model, key statistical properties like delay/angular/Doppler power spectrum density (PSD), space-time correlation function (STCF), stationary interval, and root mean square (RMS) Doppler/delay spreads in multi-scenarios are derived. The usefulness and accuracy of the proposed model are demonstrated by comparing theoretical results, simulation results, and corresponding measurement results. [ABSTRACT FROM AUTHOR]

Ionospheric delay is one of the main sources of error in satellite positioning and navigation. Ionospheric broadcast parameters are required to correct for the ionospheric delay, especially in the case of massive single-frequency users. The well-known Klobuchar model has been providing the ionospheric delay corrections for GPS users during the last several decades. For Galileo users, a three-dimensional electron density model (NeQuick G) based on the NeQuick climatological model is used to correct for ionospheric delay. The recently completed Chinese BeiDou Satellite Navigation System (BDS) broadcasts two types of ionospheric models coefficients on different signals. In this article, we propose a simplified worldwide ionospheric model (SWIM) for satellite positioning. By comparison, our SWIM model has better performance than the Klobuchar model in terms of accuracy at both low and high solar activity, and is comparable to the NeQuick G and BDS ionospheric models. At the same time, the SWIM model has high efficiency because of the simple calculation process. It has great potential for ionospheric delay corrections in satellite navigation and positioning. [ABSTRACT FROM AUTHOR]

In this paper, a novel space-time non-stationary three-dimensional (3D) wideband massive multiple-input multiple-output (MIMO) channel model is proposed. We then propose a ray-level process to model the spatial-temporal evolution of individual multipath components (MPCs), including near-field effects and (dis)appearance, and cluster-level large-scale fading. The proposed evolution process can flexibly control rays’ lifespans and smoothness of (dis)appearance in both space and time domains. In addition, we propose an improved Rayleigh-distance criterion to determine the most adequate wavefront for each cluster and ray. Existing models can easily implement the proposed criterion and make a more efficient use of computation resources. Also, a Gamma-Poisson mixture distribution is introduced to model the distribution of the number of clusters when multiple locations of the mobile station are considered. Key statistical properties of the channel, including the autocorrelation function (ACF), Doppler power spectral density (PSD), spatial cross-correlation function (S-CCF), and frequency correlation function (FCF), are derived and the impact of the ray-level evolution process on them is analyzed. We demonstrate the correctness of the derived statistical properties through numerical and simulation results. [ABSTRACT FROM AUTHOR]

Indium gallium nitride (InGaN) vertical-cavity surface-emitting lasers (VCSELs) with top dielectric and bottom pipe-gallium nitride (GaN) distributed Bragg reflectors (DBRs) were demonstrated. Pipe-GaN DBR structure consisted of a lateral wet-etched pipe-GaN layer and a GaN layer in the 20 pair stack structure as an embedded reflector. The optical birefringence behavior of the anisotropic pipe-GaN structure induced the polarization properties in the reflectance and electroluminescence (EL) spectra. Polarization EL emission peaks with narrow line-widths were measured at 430.8 nm (perpendicular to pipe-GaN) and 432.5 nm (along with pipe-GaN), respectively. The EL emission peaks with high polarization ratios were observed due to the short resonance cavity effect with the birefringence pipe-GaN DBR structure. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communication is now being considered as one of possible technologies for the sixth generation (6G) wireless communication systems. In this paper, a novel three-dimensional (3D) space-time-frequency non-stationary theoretical channel model is first proposed for 6G THz wireless communication systems employing ultra-massive multiple-input multiple-output (MIMO) technologies with long traveling paths. Considering frequency-dependent diffuse scattering, which is a special property of THz channels different from millimeter wave (mmWave) channels, the relative angles and delays of rays within one cluster will evolve in the frequency domain. Then, a corresponding simulation model is proposed with discrete angles calculated using the method of equal area (MEA). The statistical properties of the proposed theoretical and simulation models are derived and compared, showing good agreements. The accuracy and flexibility of the proposed simulation model are demonstrated by comparing the simulation results of the relative angle spread and root mean square (RMS) delay spread with corresponding measurements. [ABSTRACT FROM AUTHOR]

LiDAR footprint, defined as the illumination area of LiDAR sensor on the ground, is the fundamental unit that the sensor collects information from. The design of footprint size crucially influences the acquired LiDAR signals. For large-footprint full-waveform LiDAR, a well-designed footprint size is indispensable to acquire accurate and complete vertical profiles of scene targets. The methods that design the footprint size are increasingly needed to satisfy various application requirements. In this study, an analytical method to designing the footprint size is proposed for forest and topography applications. It is established based on a mixture Gaussian model and the designed footprint size ensures the signals of vegetation and ground can be completely extracted. Experiment results with our method show that the footprint size is preferably in the range of 10.6–25.0 m for forest application, while it is less than 32.3 m for topography application. The intersection of the two sets satisfies both applications. Furthermore, a series of sensibility studies were performed to analyze the influence of multiple key parameters to the optimal footprint size, including the scene characteristics, instrumental configurations, and application requirements. This study provides a theoretical basis for the design of future large-footprint full-waveform laser altimeters. [ABSTRACT FROM AUTHOR]

A commonly used assumption in the existing unmanned aerial vehicle (UAV) channel models is that the UAV flies along linear trajectories. However, this assumption does not always hold in realistic UAV communication scenarios. In this paper, we relax the linear trajectory restriction and present a temporally non-stationary channel model for UAV-to-ground communication scenario. The temporal non-stationarity of the channel stemming from time-varying heading directions of the UAV is properly modeled. This is achieved by combining a geometry-based stochastic model (GBSM) and an aeronautic random mobility model (RMM), which is introduced to characterize the movement pattern of UAVs. Based on UAV and ground station (GS) trajectories, time-varying model parameters and statistics including space-time-frequency correlation function (STF-CF), Doppler power spectrum density (PSD), delay PSD, and stationary interval are derived. The influences of the RMM-related parameters on the statistics are presented and analyzed. Some of those statistics are verified by measurements, showing the practicability of the model. The work presented in this paper is helpful in designing UAV communication system considering realistic UAV trajectories. [ABSTRACT FROM AUTHOR]

This paper proposes a data-driven chance-constrained optimal gas-power flow (OGPF) calculation method without any prior assumption on the distribution of uncertainties of wind power generation. The Gaussian mixture model is employed to fit the uncertainty distribution, where the Bayesian nonparametric Dirichlet process is adopted to tune the component number. To facilitate the online application of the proposed methods, an online-offline double-track distribution construction approach is established, where the frequency of training the relatively time-consuming Dirichlet process Gaussian mixture model can be reduced. On account of the quadratic gas consumption expression of gas-fired generators as well as the linear decision rule based uncertainty mitigation mechanism, the chance constraints would become quadratic ones with quadratic terms of uncertainties, which makes the proposed model more intractable. An equivalent linear separable counterpart is then provided for the quadratic chance constraints, after which the intractable chance constraints could be converted into traditional linear ones. The convex-concave procedure is used to crack the nonconvex Weymouth equation in the gas network and the auxiliary quadratic equalities. Simulation results on two test systems validate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Frequency nonstationarity is an important statistical property of beyond fifth generation wireless communication channels due to extremely large bandwidths used in millimeter wave (mmWave) and teraherz communications. In this article, a general averaged power delay profile method is first introduced as a metric to determine the stationarity regions of wireless channels in the time, frequency, and spatial domains. Then, we apply this method to determine the frequency stationarity regions (FSRs) of channel measurements in a sub-6-GHz frequency band (2–4 GHz) and two mmWave frequency bands (14–16 GHz and 28–30 GHz). Frequency nonstationary (FnS) properties are found from all of the three bands. A novel FnS channel model is then proposed to model wireless channels in all frequency bands. We first split a FnS channel into a few frequency stationary (FS) subband channels and model them one by one, which are finally combined as an FnS channel model considering the cluster evolution in the frequency domain and the frequency consistency of subband channels. Simulation results show that the frequency correlation functions of the proposed FnS channel model fit well those of the measured FnS channels. [ABSTRACT FROM AUTHOR]

The increasing integration of uncertain and volatile renewable power generation poses challenges to the operation of the interdependent electricity and gas markets. In this paper, a robust operational equilibrium solution method for the interactive markets of power and gas systems is proposed, where the bidirectional interactions include both firm energy and reserve contracting, and the impacts of the uncertainties of wind generation outputs on the two markets are characterized. The line pack as well as bidirectional flow characteristics of gas pipelines are depicted in the gas system model so as to improve its operational flexibility. To guarantee the robustness of market equilibrium against uncertainties, the power and gas market clearing models become two-stage robust ones. Column-and-constraint generation (C&CG) based and the best response algorithms are devised to clear the two markets as well as to coordinate them, respectively. Simulation results validate the effectiveness of the proposed robust operational equilibrium model and the performance of the devised solution methodology. [ABSTRACT FROM AUTHOR]

The more-electric aircraft concept has made the extraction of electrical power from both high-pressure shaft and low-pressure shaft of the aircraft engine essential for future aircraft. With each shaft driving one electrical generation channel, an advanced dual-channel enhanced power generation system can be formed. This article aims to address the power quality issues of this dual-channel power generation system, specifically focusing on the reduction of harmonics on a common dc bus. A simplified model to estimate second carrier harmonic of dc current in two-level converters is developed and reveals the fact that while this second carrier harmonic component magnitude can be determined by modulation index and dc-link current, its phase angle is solely dependent on the angle of carrier signals. Based on the developed model and these key findings, a new harmonic cancellation method is proposed through active power sharing and phase angle shifting of the carrier signals within different power sources. The method has demonstrated high robustness and is effective under different fundamental frequencies and power sharing ratio. Both simulation and experimental results are presented in this article to validate the proposed harmonic model and the enhanced cancellation method. [ABSTRACT FROM AUTHOR]

This paper presents the growth law of electrical tree in glass/epoxy resin composite (GER). Two influencing factors on electrical tree growth, the relative permittivity of the glass and the adhesion type of the interface, are investigated. An improved WZ model is built to further explore the mechanism of electrical tree growth in GER. The electric field between the needle electrode and the glass is enhanced when the relative permittivity of glass is higher than that of epoxy resin, which is responsible for the attractive effect of the glass. The breakdown strength of the interface determines the growth mode of electrical tree. When the breakdown strength of the interface is as low as the air gap, the electrical tree showed ‘linear growth’ at the interface. High breakdown strength of the interface lead to ‘step growth’ of electrical tree and prolong the growth time compared to ‘linear growth’. [ABSTRACT FROM AUTHOR]

This paper proposes a data-driven adjustable robust unit commitment (UC) model for integrated electric-heat systems (IEHSs), where the data-driven, and robustness adjustable features are endowed by the novel uncertainty modeling method. The devised uncertainty set is the intersections of a series of hyperplanes. It combines the merits of the traditional box-like uncertainty set, whose underlying computation burden is moderate, and the convex hull formed by historical data, which would lead to less conservative operation strategies. The boundaries of the bounding high-dimensional rectangle of the uncertainty set are set as decision variables to achieve the balance between the operation costs, and risk. The two-stage decision-making framework is employed in the robust UC model of IEHSs, in which the district heating networks are operated at the variable-flow-variable-temperature mode. The modified column-and-constraint generation (C, and CG) algorithm is employed to solve the proposed robust program, where an additional feasible region reduction step is embedded to decrease the computation burden of the worst case identification. Simulation results on two test systems verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this article, we propose a transformation method to model space-time-variant (STV) two-dimensional non-stationary wideband massive multiple-input multiple-output (MIMO) channels. This method enables us to obtain the STV joint probability density function of the time of arrival and angle of arrival (AOA) at any time instant and antenna element of the array from a predefined configuration of the scatterers. In addition, we introduce a simplified channel modeling approach based on STV parameters of the AOA distribution and demonstrate that key statistical properties of massive MIMO channels, such as the STV temporal autocorrelation function and Doppler power spectral density, can be derived in closed form. As examples of application, we study multiple array-variant properties of three widely-used geometry-based stochastic models (GBSMs): the Unified Disk, Ellipse, and Gaussian scattering models. Furthermore, we present numerical and simulation results of the statistical properties of these three GBSMs and compare them with those obtained using the conventional spherical wavefront approach. We point out possible limitations of the studied channel models to properly represent massive MIMO channels. [ABSTRACT FROM AUTHOR]

This work presents a rate equation model for interband cascade lasers, which is used for investigating modulation dynamics and optical noise properties. Through standard small-signal analysis of the rate equations, we analytically derive the resonance frequency, the damping factor, the relative intensity noise (RIN), and the frequency noise (FN) of the interband cascade lasers. It is shown that more cascading stages are beneficial for reaching a broad modulation bandwidth at a low pump current. On the other hand, fewer cascading stages are favorable to achieve low-RIN and low-FN (or narrow-linewidth) laser emission. [ABSTRACT FROM AUTHOR]

Canopy height models (CHMs) were utilized to detect treetops and estimate individual-tree parameters. The treetop detection based on CHMs was affected by surface topography and crown characteristics. However, their effects have not been well studied. Therefore, this paper aimed at assessing the impacts of aforementioned factors to facilitate treetop identification from LiDAR-derived CHMs. To fulfill this objective, we first extended and improved the previous models for cases with various terrains. Then, a new theoretical model was developed to quantify treetop displacements for ellipsoidal tree crowns. Finally, we further analyzed the treetop displacements due to terrain slope, crown radius, crown shape, and offset distance to the slope surface. Our analysis indicates that the vertical displacement increases exponentially with terrain slope; thus, the effect of terrain slope must be considered over extremely steep areas; larger errors are observed for trees with a large crown radius; the treetop displacements are highly correlated with crown shape, the effect of topographic normalization can be neglected for conical crowns with a large crown angle, and the elliptical crown shape can reduce the treetop detection errors; and treetop displacements increases with offset distance to the slope surface in , while opposite results are observed in. In addition, the results also demonstrate that the effect of slope-distorted CHMs may be quite different for different types of tree crowns and terrains. Overall, this paper makes a significant contribution to the development of theoretical models for quantifying treetop displacements. Furthermore, our findings provide a theoretical basis and guidance for better identifying treetops from LiDAR-derived CHMs. [ABSTRACT FROM AUTHOR]

The fast developments of high-speed train (HST) and growing communication demands of users pose new challenges for HST communication systems. To provide reliable communication services, key 5G communication technologies, such as millimeter-wave (mmWave) and massive multiple-input multiple-output (MIMO), and potential architectures, such as coordinated multipoint and mobile relay station, are considered in future railway communications. New technologies and architectures will bring new channel propagation characteristics. Accurate channel models that can capture these channel characteristics play a critical role in the design and test of future railway communication systems. This article reviews the HST channel measurements conducted in different scenarios and frequency bands, and the advanced HST channel models. Then a novel HST channel model incorporating the mmWave and massive MIMO propagation characteristics is presented, and its frequency non-stationarity is analyzed. Finally, some future directions are discussed. [ABSTRACT FROM AUTHOR]

The guaranteed-performance consensualization for high-order linear and nonlinear multiagent systems with switching topologies is respectively realized in a completely distributed manner in the sense that consensus design criteria are independent of interaction topologies and switching motions. This paper first proposes an adaptive consensus protocol with guaranteed-performance constraints and switching topologies, where interaction weights among neighboring agents are adaptively adjusted and state errors among all agents can be regulated. Then, a new translation-adaptive strategy is shown to realize completely distributed guaranteed-performance consensus control and an adaptive guaranteed-performance consensualization criterion is given on the basis of the Riccati inequality. Furthermore, an approach to regulate the consensus control gain and the guaranteed-performance cost is proposed in terms of linear matrix inequalities. Moreover, main conclusions for linear multiagent systems are extended to Lipschitz nonlinear cases. Finally, two numerical examples are provided to demonstrate theoretical results. [ABSTRACT FROM AUTHOR]

High-speed rail public broadband wireless access requires communication terminals with high mobility to perform seamless cell switching in a harsh and fast time-varying environment. However, frequent switching caused by fast motion inevitably leads to unpredictable high volatility of the available spectrum, resulting in inefficient wireless communication. The application of highly mobile cognitive radio technology may address this challenge. This paper first analyzes the physical structure of the existing railway wireless communication network, and determines the characteristics of chainlike distribution and cascade operation of the base stations along the railway. Furthermore, using Bayesian reinforcement learning and multi-agent theory, a distributed cognitive base station model suitable for railway wireless environment is constructed. Based on the joint spectrum management of cascaded base station groups, this model proposes a multi-agent coordination algorithm with the goal of global optimal communication performance of the entire rail line. Finally, this paper evaluates the network performance of various test scenarios, and proves that the cognitive base station multi-agent cascade cooperative system can significantly increase the probability of successful data transmission and greatly reduce wireless spectrum handovers. This proposed scheme provides a brand-new solution for solving the problem of low wireless spectrum efficiency in the typical railway wireless network. [ABSTRACT FROM AUTHOR]

A fully integrated 93.4–104.8-GHz 57-mW fractional- ${N}$ cascaded phase-locked loop (PLL) with true in-phase injection-coupled quadrature voltage-controlled oscillator (QVCO) is reported. By cascading the fractional- ${N}$ PLL and the subsampling PLL, good phase noise, high resolution, and wide acquisition range are achieved simultaneously. The transformer-based true in-phase injection coupled technique is adopted in the QVCO to obtain both low phase noise and low-power consumption. The proposed cascaded PLL was fabricated in a 65-nm CMOS technology with silicon size of 0.88 mm2. The measured phase noise of QVCO and PLL is −113.26 and −106.63 dBc/Hz at 10-MHz offset, respectively. The FOM and FOMT of the QVCO at 10-MHz offset are −178.4 and −180.0 dBc/Hz, respectively. The frequency resolution of the 100-GHz output is less than 3.6 kHz. [ABSTRACT FROM AUTHOR]

Gas-fired units and power-to-gas facilities provide pivotal backups for power systems with volatile renewable generations. The deepened system interdependence calls for elaborate consideration of network models of both natural gas and power systems, as well as uncertain factors. This paper proposes a data-driven distributionally robust optimization model for the optimal gas-power flow problem with uncertain wind generation. The concept of zonal line pack and line pack reserve are raised to topologically distinguish fuel suppliers of gas-fired units and ensure gas system operating security during reserve deployment. Wind power uncertainty is described by an ambiguity set, i.e., a family of candidate distributions around an empirical distribution in the sense of Wasserstein distance. A convex optimization-based solution procedure is developed, which entails solving only second-order cone programs. Computational results validate the effectiveness of the proposed models and methods. [ABSTRACT FROM AUTHOR]

The cascaded H-bridge (CHB) converter has become a promising candidate topology for utility-scale photovoltaic systems thanks to merits like modular structure, distributed maximum power point tracking (MPPT), and direct distribution grid access without medium-voltage transformers. However, module mismatches arising from nonideal elements like partial shading and parameter variations pose a technical challenge for such systems. If not dealt with properly, module mismatches can lead to adverse effects like unbalanced dc-link voltages of the modules, distortion of grid current, and reduced power generation. Conventional methods, such as reactive power compensation and level-shifted pulsewidth modulation (LS-PWM) based compensation, can alleviate this issue, but their performances are still limited by the allowable modulation range of power converters. In this paper, a compensation strategy combining reactive power compensation with a novel modulation method is proposed to extend the operating range in terms of module mismatch. Experimental results on a 2.4 kW/208 V single-phase setup are presented and have demonstrated that the proposed method can not only ride through a larger range of module mismatches but also improve solar power utilization and system efficiency owing to reduced switching events, noncompromised MPPT, and less required reactive power. [ABSTRACT FROM AUTHOR]

As a typical latent factor model, Matrix Factorization (MF) has demonstrated its great effectiveness in recommender systems. Users and items are represented in a shared low-dimensional space so that the user preference can be modeled by linearly combining the item factor vector $V$ using the user-specific coefficients $U$ . From a generative model perspective, $U$ and $V$ are drawn from two independent Gaussian distributions, which is not so faithful to the reality. Items are produced to maximally meet users’ requirements, which makes $U$ and $V$ strongly correlated. Meanwhile, the linear combination between $U$ and $V$ forces a bijection (one-to-one mapping), which thereby neglects the mutual correlation between the latent factors. In this paper, we address the upper drawbacks, and propose a new model, named Correlated Matrix Factorization (CMF). Technically, we apply Canonical Correlation Analysis (CCA) to map $U$ and $V$ into a new semantic space. Besides achieving the optimal fitting on the rating matrix, one component in each vector ($U$ or $V$ ) is also tightly correlated with every single component in the other. We derive efficient inference and learning algorithms based on variational EM methods. The effectiveness of our proposed model is comprehensively verified on four public datasets. Experimental results show that our approach achieves competitive performance on both prediction accuracy and efficiency compared with the current state of the art. [ABSTRACT FROM AUTHOR]

Basic kinetic process of plasmas is studied by a first principle based N-body simulation. By confirming Coulomb collisional relaxation process, this paper is extended to investigate the dynamics of Debye shielding. Some of the key numerical techniques are discussed, including how to avoid singularities at the near encounter of two charged particles. Electron distribution function in Debye shielding is revealed, which deviates from conventional Maxwellian distribution function. [ABSTRACT FROM AUTHOR]

This paper presents a novel high voltage conversion ratio (HVCR) bidirectional CLTC resonant dc–dc converter. Based on inductor-inductor-capacitor (LLC), series resonant converter, and capacitor-inductor-inductor-capacitor (CLLC), the novel CLTC structure is proposed. With the use of auxiliary transformer and extra resonant capacitor, a CLTC resonant dc–dc converter can achieve zero voltage switching in all load ranges. Also, CLTC has a good gain characteristic with high power load. In this study, a review of the statuses for the isolated HVCR bidirectional converters is made. The operating principle of a bidirectional power flow in two directions is analyzed in details. In addition, by changing ac output resistance, a modified fundamental harmonic analysis (FHA) method makes the calculated gain curve more accurately than traditional FHA. Also, voltage and current stresses of power switches and resonant capacitors are given. A parameter optimization method is proposed to minimize the impedance angle of CLTC, which corresponds to less reactive power and turn-off current. The optimal parameters show advantages in voltage and current stresses. Moreover, power losses are analyzed in this study, showing advantage of CLTC in efficiency. At last, the experimental results based on a 5-kW prototype converter are presented to validate the theoretical analyses. [ABSTRACT FROM AUTHOR]

In intelligent vehicular communication networks, a hybrid communication architecture is used which combines both centralized and ad hoc transmission schemes. In order to maximize the end-to-end delivery ratio while reducing the network overhead, one important problem is to efficiently design the data forwarding algorithm to guarantee the quality of data transmission. In this paper, by considering the traveling information and vehicular space-crossing community structure, two metrics, “space–time approachability” and “social approachability,” are defined to provide the absolute and relative geographical information of the forthcoming contacts, respectively. Then, a novel data-forwarding algorithm, called approachability-based algorithm, is proposed, which utilizes two metrics together for better routing quality. We evaluate the proposed approachability-based algorithm utilizing San Francisco Cabspotting and Shanghai Taxi Movement datasets. Simulation results show that the approachability-based data forwarding algorithm can achieve better performance than the popular data forwarding algorithms ZOOM and BUBBLE RAP in all the interested scenarios. [ABSTRACT FROM PUBLISHER]

In this paper, new enhanced cognitive radio networks (E-CRNs) based on spectrum sharing (SS) and spectrum aggregation (SA) are proposed for fifth generation (5G) wireless networks. The E-CRNs jointly exploit the licensed spectrum shared with the primary user (PU) networks and the unlicensed spectrum aggregated from the industrial, scientific, and medical bands. The PU networks include TV systems in TV white space and different incumbent systems in the long term evolution time division duplexing bands. The harmful interference from the E-CRNs to the PU networks are delicately controlled. Furthermore, the coexistence between the E-CRNs and other unlicensed systems, such as WiFi, is studied. The E-CRNs framework including dynamic spectrum management (DSM) is designed for the key parameters of licensed SS and unlicensed SA. The essential tradeoff between sharing efficiency and aggregation efficiency for the E-CRNs is discussed. Based on this tradeoff, a spectrum lean-management scheme is proposed to fulfill the DSM. Moreover, a water-filling algorithm is designed to dynamically access the available spectrum. Numerical results demonstrate that the proposed E-CRNs can significantly improve the system performance in terms of data rate, outage probability, and spectrum efficiency. In particular, the E-CRNs framework provides a spectrum usage prototype for 5G wireless communication networks. [ABSTRACT FROM AUTHOR]

The accurate estimation of within-footprint slope is very important for measuring earth’s surface characteristics using satellite light detection and ranging (LiDAR) data. Several models have previously been proposed for slope estimation; however, these models have limitations in either accuracy or applicability. Therefore, the main purpose of this paper is to explore the influence of various factors (e.g., ground vertical extent, footprint size, footprint shape, and footprint orientation) on slope estimation to better estimate the within-footprint slope using large-footprint waveform LiDAR data. The results indicated that the absolute slope error due to the coupling effect of ground vertical extent and footprint size increased with an increase in the ratio of ground vertical extent and footprint size, while the relative slope error had an opposite trend. The slope error caused by footprint shape was relatively low when the footprint eccentricity was small. However, the slope error due to footprint shape grew rapidly when the footprint eccentricity became larger; thus, it is essential to fully take into account the influence of footprint shape on within-footprint slope estimation. In addition, the results suggest that the slope error changed regularly based on the intersection angle between footprint orientation and terrain aspect. This paper also provided guidance for the determination of an easy and practical model for within-footprint slope estimation. The determination of best model is dependent on the value of intersection angle. Once the intersection value is given, the best model can easily be determined. Using the best model, the within-footprint terrain slope can be estimated with high accuracy. [ABSTRACT FROM AUTHOR]

In this paper, we propose a risk-based data-driven distributionally robust approach to investigating the optimal power flow with dynamic line rating. The risk terms, including penalties for load shedding, wind generation curtailment and line overload, are embedded into the objective function. To robustify the solution, we consider a distributional uncertainty set based on the second-order moment, that captures the correlation between wind generation outputs and line ratings, and also the Wasserstein distance, that hedges against data perturbations. We show that the proposed model can be reformulated as a convex conic program. Approximations of the proposed model are suggested, which leads to a significant reduction of the number of the constraints. For practical large-scale test systems, a distributionally robust optimal power flow model with Wasserstein-distance-based distributional uncertainty set and its convex reformulation are also provided. Simulation results on the 5-bus, the IEEE 118-bus and the Polish 2736-bus test systems validate the effectiveness of the proposed models. [ABSTRACT FROM AUTHOR]

The increasing interdependencies between natural gas systems and power systems create new business opportunities in coupled energy distribution markets. This paper studies the marginal price based bilateral energy trading on the equilibrium of coupled natural gas and electricity distribution markets. Convex relaxation is employed to solve a multiperiod optimal power flow problem, which is used to clear the electricity market. A successive second-order cone programming approach is utilized to solve a multiperiod optimal gas flow problem, which is used to clear the gas market. In addition, the line pack effect in the gas network is considered, which can offer storage capacity and provide extra operation flexibility for both networks. In both problems, locational marginal energy prices are recovered from the Lagrangian multipliers associated with nodal balancing equations. Furthermore, a best-response decomposition algorithm is developed to identify the equilibrium of the coupled energy markets with bilateral gas and electricity trading, which leverages the computational superiority of SOCPs. Cases studies on two test systems validate the proposed methodology. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) is an emerging nascent research area having enormous application prospects. Efficient evaluation methods are critical requirements for implementing high-performance VLC systems. Most research just focus on system analyses from optical channels, modulation methods, or communication theories. However, the basic theoretical analyses of the relationships between hardware circuit current energy and optical power are absent. This paper makes up for this deficiency. Based on a general VLC communication scenario, we theoretically analyze the transferring procedures between circuit current energy and optical power. The current energy transferring calculation model (CETCM) and CET parameters are proposed for the first time. The peak current energy response, current energy gain, threshold of optical power transferring distance, and current signal-to-noise ratio can be calculated by the CETCM and CET parameters. Experiments show that they can comprehensively reflect the communication characteristics of practical VLC system, and are quite important and valuable for VLC system evaluations, implementations, and optimizations. [ABSTRACT FROM AUTHOR]

Using mobile Light Detection and Ranging point clouds to accomplish road scene labeling tasks shows promise for a variety of applications. Most existing methods for semantic labeling of point clouds require a huge number of fully supervised point cloud scenes, where each point needs to be manually annotated with a specific category. Manually annotating each point in point cloud scenes is labor intensive and hinders practical usage of those methods. To alleviate such a huge burden of manual annotation, in this paper, we introduce an active learning method that avoids annotating the whole point cloud scenes by iteratively annotating a small portion of unlabeled supervoxels and creating a minimal manually annotated training set. In order to avoid the biased sampling existing in traditional active learning methods, a neighbor-consistency prior is exploited to select the potentially misclassified samples into the training set to improve the accuracy of the statistical model. Furthermore, lots of methods only consider short-range contextual information to conduct semantic labeling tasks, but ignore the long-range contexts among local variables. In this paper, we use a higher order Markov random field model to take into account more contexts for refining the labeling results, despite of lacking fully supervised scenes. Evaluations on three data sets show that our proposed framework achieves a high accuracy in labeling point clouds although only a small portion of labels is provided. Moreover, comparative experiments demonstrate that our proposed framework is superior to traditional sampling methods and exhibits comparable performance to those fully supervised models. [ABSTRACT FROM AUTHOR]

Pulsed power load (PPL) consumes a huge amount of energy within a very short period of time. Directly connecting a PPL to a shipboard power system (SPS) will cause large disturbance even instability during PPL deployment. As an important category of energy storage system (ESS), the flywheel ESS (FESS) is an ideal source for PPL accommodation. By powering the PPL separately with a sufficiently charged FESS, the negative impacts of PPL on SPS can be avoided. The paper presents an adaptive output-constrained control design that can realize fast charging of the FESS and simultaneously minimize the disturbance to system frequency. Major benefit of the algorithm is that transient response can be guaranteed to stay within user-defined, time-varying bounds. This property makes the algorithm different from typical adaptive control algorithms and very appealing for high-performance applications. By applying the standard Lyapunov synthesis, all closed-loop signals are proved to be bounded. Finally, the proposed control design is tested through simulations using SPS models with different details. Simulation results demonstrate the effectiveness of the proposed control design. [ABSTRACT FROM AUTHOR]

This paper proposes a novel quadrature space-frequency index modulation (QSF-IM) scheme as a promising energy-efficient radio-access technology for the fifth generation (5G) wireless systems. Motivated by the potential energy saving of spatial modulation (SM) with the part of information being carried through antenna indexes, the proposed scheme further leverages the benefits of SM by applying the idea across the spatial and frequency domains. Moreover, by deploying dual antenna constellation for in-phase and quadrature-phase transmission, the proposed scheme can enhance data rate at no extra cost of energy consumption, leading to further improvement in energy efficiency. Theoretical bit error rate and achievable sum-rate of the proposed scheme over frequency-selective correlated Rician and Rayleigh fading channels are derived and are shown to have good agreement with simulations. Furthermore, the effectiveness of the proposed scheme is analyzed through a comprehensive list of performance metrics, including spectral efficiency (SE), energy efficiency (EE), cost efficiency (CE), and economic efficiency. Performance trade-offs between these metrics are thoroughly investigated. Compared with other existing schemes, the proposed QSF-IM scheme is demonstrated to offer better EE-SE and EE-CE tradeoffs, and can therefore be considered as a potential candidate for energy-spectral efficient 5G systems. [ABSTRACT FROM AUTHOR]

A novel unified framework of geometry-based stochastic models for the fifth generation (5G) wireless communication systems is proposed in this paper. The proposed general 5G channel model aims at capturing small-scale fading channel characteristics of key 5G communication scenarios, such as massive multiple-input multiple-output, high-speed train, vehicle-to-vehicle, and millimeter wave communications. It is a 3-D non-stationary channel model based on the WINNER II and Saleh-Valenzuela channel models considering array-time cluster evolution. Moreover, it can easily be reduced to various simplified channel models by properly adjusting model parameters. Statistical properties of the proposed general 5G small-scale fading channel model are investigated to demonstrate its capability of capturing channel characteristics of various scenarios, with excellent fitting to some corresponding channel measurements. [ABSTRACT FROM AUTHOR]

Document network is a kind of intriguing dataset which can provide both topical (textual content) and topological (relational link) information. A key point in modeling such datasets is to discover proper denominators beneath the text and link. Most previous work introduces the assumption that documents closely linked with each other share common latent topics. However, the heterophily (i.e., tendency to link to different others) of nodes is neglected, which is pervasive in social networks. In this paper, we simultaneously incorporate community detection and topic modeling in a unified framework, and appeal to Canonical Correlation Analysis (CCA) to capture the latent semantic correlations between the two heterogeneous factors, community and topic. Despite of the homophily (i.e., tendency to link to similar others) or heterophily, CCA can properly capture the inherent correlations which fit the dataset itself without any prior hypothesis. We also impose auxiliary word embeddings to improve the quality of topics. The effectiveness of our proposed model is comprehensively verified on three different types of datasets which are hyperlinked networks of web pages, social networks of friends, and coauthor networks of publications. Experimental results show that our approach achieves significant improvements compared with the current state of the art. [ABSTRACT FROM AUTHOR]

Link similarity is widely applied in measuring the similarity between such objects as Web pages, scientific papers, and social networks. However, there are some deficiencies in the existing methods to measure it. For example, they cannot handle some semantic-similar contents. Their computation may not lead to accurate results in some cases. This paper presents a novel method to do so. It introduces the semantic similarity to calculate the similarity between two given objects, and overcomes the drawback caused by the fact that the existing methods ignore the semantic information of objects. It also gives a novel computation function to make the computing result of similarity more accurate. [ABSTRACT FROM PUBLISHER]

The wide integration of gas-fired units and implementation of power-to-gas technologies bring increasing interdependence among the natural gas and electricity infrastructures. This paper studies the equilibrium of the coupled gas and electricity markets, which is driven by the strategic offering behaviors: each producer endeavours to maximize its own profit by taking the market clearing process into consideration. The market equilibrium can be obtained from an equilibrium problem with equilibrium constraints. A special diagonalization algorithm is devised, in which the unilateral equilibrium of the gas or electricity market is found in the inner loop given the rivals’ strategies; the interactions of the two markets are tackled in the outer loop. Case studies on two test systems validate the proposed methodology. [ABSTRACT FROM PUBLISHER]

As one of the most common features in the man-made environments, straight lines play an important role in many applications. In this paper, we present a new framework to extract line segments from large-scale point clouds. The proposed method is fast to produce results, easy for implementation and understanding, and suitable for various point cloud data. The key idea is to segment the input point cloud into a collection of facets efficiently. These facets provide sufficient information for determining linear features in the local planar region and make line segment extraction become relatively convenient. Moreover, we introduce the concept “number of false alarms” into 3-D point cloud context to filter the false positive line segment detections. We test our approach on various types of point clouds acquired from different ways. We also compared the proposed method with several other methods and provide both quantitative and visual comparison results. The experimental results show that our algorithm is efficient and effective, and produce more accurate and complete line segments than the comparative methods. To further verify the accuracy of the line segments extracted by the proposed method, we also present a line-based registration framework, which employs these line segments on point clouds registration. [ABSTRACT FROM PUBLISHER]

With a view to detecting foliage-obscured/ground-obscured targets on a global scale, low frequency (i.e., very high frequency (VHF)/ultrahigh frequency (UHF) band) and wide bandwidth is a trend in future spaceborne synthetic aperture radar (SAR) system design. However, due to the dispersion of ionosphere, VHF/UHF wide bandwidth SAR signals inevitably experience adverse effects. In contrast to narrow bandwidth SAR at VHF/UHF, quadratic and cubic ionospheric phase errors will introduce noticeable effects on future wide-bandwidth SAR systems. Traditional evaluation models based on Taylor series expansion may become inaccurate when an extremely wide bandwidth is considered. With a focus on this this issue, first, the shortcoming of Taylor series expansion of ionospheric phase errors is briefly discussed in this paper. Then, a new analytical model based on Legendre orthogonal polynomials is developed, which is expected to be widely applicable, especially for low-frequency and wide-bandwidth SAR systems. Finally, compared with previous models based on Taylor series expansion, numerical simulations and evaluations show the superiority of the new model. [ABSTRACT FROM PUBLISHER]

This paper proposes a methodology to identify and protect vulnerable components of connected gas and electric infrastructures from malicious attacks, and to guarantee a resilient operation by deploying valid corrective actions, while accounting for the interdependence of the gas pipeline network and power transmission network. The proposed mathematical formulation gives rise to to a trilevel optimization problem, where the lower level is a multiperiod economic dispatch of the gas–electric system and seeks operating strategies under available resources and given attack, the middle level distinguishes the most threatening attack on the coupled physical infrastructures, and the upper level provides optimal preventive decisions to reinforce the vulnerable components and increase the system resilience. By reformulating the lower level problem as a mixed integer linear programming, a nested column-and-constraint generation algorithm is developed to solve the min–max–min model. Case studies on two test systems demonstrate the effectiveness and efficiency of the proposed methodology. [ABSTRACT FROM AUTHOR]

A multiple-feature-based adaptive sparse representation (MFASR) method is proposed for the classification of hyperspectral images (HSIs). The proposed method mainly includes the following steps. First, four different features are separately extracted from the original HSI and they reflect different kinds of spectral and spatial information. Second, for each pixel, a shape adaptive (SA) spatial region is extracted. Third, an adaptive sparse representation algorithm is introduced to obtain the sparse coefficients for the multiple-feature matrix set of pixels in each SA region. Finally, these obtained coefficients are jointly used to determine the class label of each test pixel. Experimental results demonstrated that the proposed MFASR method can outperform several well-known classifiers in terms of both qualitative and quantitative results. [ABSTRACT FROM PUBLISHER]

The millimeter-wave (mmWave) band will be used for the fifth-generation communication systems. In this paper, 60-GHz mmWave channel measurements and modeling are carried out for indoor office environments. The rotated directional antenna-based method and uniform virtual array-based method are adopted and compared to investigate the 60-GHz channel in a 3-D space, simultaneously covering azimuth and coelevation domains. The multipath component parameters including power, delay, azimuth, and elevation angles are estimated with the space-alternating generalized expectation–maximization estimation algorithm, and then processed with the K-means clustering algorithm. An extended Saleh–Valenzuela model with both delay and angular cluster features is used to characterize the measured channel, and the intercluster and intracluster parameters are extracted. We find that the azimuth departure angles are diverse and highly related to the antenna position and measurement environment, while the elevation departure angles are more related to the antenna height difference and confined in a relatively small direction range. The azimuth angle spread is much larger than the elevation angle spread either in global level or in cluster level. The results agree with the studies in the literature and channel models in IEEE standards. [ABSTRACT FROM PUBLISHER]