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Hua Wang

Publications and source records attributed to Hua Wang.

At least 199 records · Page 11Linked to original sources
arXiv2019

A 28/37/39GHz Multiband Linear Doherty Power Amplifier in Silicon for 5G Applications

This paper presents the first multiband mm-wave linear Doherty PA in silicon for broadband 5G applications. We introduce a new transformer-based on-chip Doherty power combiner, which can reduce the impedance transformation ratio in power back-off (PBO) and thus improve the bandwidth and power-combining efficiency. We also devise a "driver-PA co-design" method, which creates power-dependent uneven feeding in the Doherty PA and enhances the Doherty operation without any hardware overhead or bandwidth compromise. For the proof of concept, we implement a 28/37/39-GHz PA fully integrated in a standard 130-nm SiGe BiCMOS process, which occupies 1.8mm2. The PA achieves a 52% -3-dB small-signal S21 bandwidth and a 40% -1-dB large-signal saturated output power (Psat) bandwidth. At 28/37/39GHz, the PA achieves +16.8/+17.1/+17-dBm Psat, +15.2/+15.5/+15.4-dBm P1dB, and superior 1.72/1.92/1.62 times efficiency enhancement over class-B operation at 5.9/6/6.7-dB PBO. Moreover, the PA demonstrates multi-Gb/s data rates with excellent efficiency and linearity for 64QAM in all the three 5G bands. This PA advances the state of the art for Doherty, wideband, and 5G silicon PAs in mm-wave bands. It supports drop-in upgrade for current PAs in existing mm-wave systems and opens doors to compact system solutions for future multiband 5G massive MIMO and phased-array platforms.

eess.SP↗
arXiv2019

Spherical Principal Component Analysis

Principal Component Analysis (PCA) is one of the most important methods to handle high dimensional data. However, most of the studies on PCA aim to minimize the loss after projection, which usually measures the Euclidean distance, though in some fields, angle distance is known to be more important and critical for analysis. In this paper, we propose a method by adding constraints on factors to unify the Euclidean distance and angle distance. However, due to the nonconvexity of the objective and constraints, the optimized solution is not easy to obtain. We propose an alternating linearized minimization method to solve it with provable convergence rate and guarantee. Experiments on synthetic data and real-world datasets have validated the effectiveness of our method and demonstrated its advantages over state-of-art clustering methods.

cs.LG↗
arXiv2019

Crowd Behavior Simulation with Emotional Contagion in Unexpected Multi-hazard Situations

In this paper we present a novel crowd simulation method by modeling the generation and contagion of panic emotion under multi-hazard circumstances. Specifically, we first classify hazards into different types (transient and persistent, concurrent and non-concurrent, static and dynamic ) based on their inherent characteristics. Then, we introduce the concept of perilous field for each hazard and further transform the critical level of the field to its invoked-panic emotion. After that, we propose an emotional contagion model to simulate the evolving process of panic emotion caused by multiple hazards in these situations. Finally, we introduce an Emotional Reciprocal Velocity Obstacles (ERVO) model to simulate the crowd behaviors by augmenting the traditional RVO model with emotional contagion, which combines the emotional impact and local avoidance together for the first time. Our experimental results show that this method can soundly generate realistic group behaviors as well as panic emotion dynamics in a crowd in multi-hazard environments.

cs.MA↗
arXiv2019

Variations of the eccentricity and their properties in trees

Motivated from the study of eccentricity, center, and sum of eccentricities in graphs and trees, we introduce several new distance-based global and local functions based on the smallest distance from a vertex to some leaf (called the `uniformity' at that vertex). Some natural extremal problems on trees are considered. Then the middle parts of a tree is discussed and compared with the well-known center of a tree. The values of the global functions are also compared with the sum of eccentricities and some sharp bounds are established. Last but not the least, we show that the difference between the eccentricity and the uniformity, when considered as a local function, behaves in a very similar way as the eccentricity itself.

math.CO↗
arXiv2019

Scattering and blow-up criteria for 3D cubic focusing nonlinear inhomogeneous NLS with a potential

In this paper, we consider the 3d cubic focusing inhomogeneous nonlinear Schrödinger equation with a potential $$ iu_{t}+Δu-Vu+|x|^{-b}|u|^{2}u=0,\;\;(t,x) \in {\bf{R}\times{\bf{R}}^{3}}, $$ where $0 \mathcal{K}$ if $V$ satisfies some additional assumptions.0}\|_{L^{2}}^{2(1-s_{c})}\|H^{\frac{1}{2}}u_{0}\|_{L^{2}}^{2s_{c}}>\mathcal{K}$ if $V$ satisfies some additional assumptions.

math.AP↗
arXiv2018

Odd Fibbinary Numbers and the Golden Ratio

The fibbinary numbers are positive integers whose binary representation contains no consecutive ones. We prove the following result: If the $j$th odd fibbinary is the $n$th \emph{odd} fibbinary number, then $j = \lfloor nϕ^2 \rfloor - 1.$

math.CO↗
arXiv2018

Dynamics of the focusing 3D cubic NLS with slowly decaying potential

In this paper, we consider a 3d cubic focusing nonlinear Schrödinger equation (NLS) with slowing decaying potentials. Adopting the variational method of Ibrahim-Masmoudi-Nakanishi \cite{IMN}, we obtain a condition for scattering. It is actually sharp in some sense since the solution will blow up if it's false. The proof of blow-up part relies on the method of Du-Wu-Zhang \cite{DWZ}

math.AP↗
arXiv2018

Quantum Nonlinear Ferroic Optical Hall Effect

Nonlinear optical responses to external electromagnetic field, characterized by second and higher order susceptibilities, play crucial roles in nonlinear optical devices and novel optoelectronics. Herein we present a quantum nonlinear ferroic optical Hall effect (QNFOHE) in multiferroics - a Hall-like direct photocurrent originated from the second order current response to intense electromagnetic field whose direction can be controlled by both internal ferroic orders and external light polarization. QNFOHE consists of two types of nonlinear photocurrent responses - shift current and circular photocurrent under linearly and circularly polarized light irradiation dominated by topological shift vector and Berry curvature, respectively. We elucidate the microscopic mechanism of QNFOHE in a representative class of 2D multiferroic materials using group theoretical analyses and first-principles electronic structure theory. The complex interplay of crystalline, permutation, gauge, and time reversal symmetries as well as inherent causality governs the symmetry properties of shift current and circular photocurrent. QNFOHE combined with rich ferroic degrees of freedom in multiferroic materials will open up a variety of new avenues for realizing tunable and configurable nonlinear optoelectronics etc.

cond-mat.mes-hall↗
arXiv2018

Scattering and blowup for $L^{2}$-supercritical and $\dot{H}^{2}$-subcritical biharmonic NLS with potentials

We mainly consider the focusing biharmonic Schrödinger equation with a large radial repulsive potential $V(x)$: \begin{equation*} \left\{ \begin{aligned} iu_{t}+(Δ^2+V)u-|u|^{p-1}u=0,\;\;(t,x) \in {\bf{R}\times{\bf{R}}^{N}}, u(0, x)=u_{0}(x)\in H^{2}({\bf{R}}^{N}), \end{aligned}\right. \end{equation*} If $N>8$, \ $1+\frac{8}{N} N+4$, then we firstly prove a global well-posedness and scattering result for the radial data $u_0\in H^2({\bf R}^N)$ which satisfies that $$ M(u_0)^{\frac{2-s_c}{s_c}}E(u_0) \|Q\|^{\frac{2-s_c}{s_c}}_{L^{2}}\|ΔQ\|_{L^{2}}. $$

math.AP↗
arXiv2018

Wideband Hybrid Precoding for Next-Generation Backhaul/Fronthaul Based on mmWave FD-MIMO

Millimeter-wave (mmWave) communication is considered as an indispensable technique for the next-generation backhaul/fronthaul network thanks to its large transmission bandwidth. Especially for heterogeneous network (HetNet), the mmWave full-dimension (FD)-MIMO is exploited to establish the backhaul/fronthaul link between phantom-cell base stations (BSs) and macro-cell BSs, where an efficient precoding is prerequisite. Against this background, this paper proposes a principle component analysis (PCA)-based hybrid precoding for wideband mmWave MIMO backhaul/fronthaul channels. We first propose an optimal hybrid precoder by exploiting principal component analysis (PCA), whereby the optimal high dimensional frequency-selective precoder are projected to the low-dimensional frequency-flat precoder. Moreover, the combiner is designed by leveraging the weighted PCA, where the covariance of received signal is taken into account as weight to the optimal minimum mean square error (MMSE) fully-digital combiner for further improved performance. Simulations have confirmed that the proposed scheme outperforms conventional schemes in spectral efficiency (SE) and bit-error-rate (BER) performance.

cs.IT↗
arXiv2018

Machine Learning Based Hybrid Precoding for MmWave MIMO-OFDM with Dynamic Subarray

Hybrid precoding design can be challenging for broadband millimeter-wave (mmWave) massive MIMO due to the frequency-flat analog precoder in radio frequency (RF). Prior broadband hybrid precoding work usually focuses on fully-connected array (FCA), while seldom considers the energy-efficient partially-connected subarray (PCS) including the fixed subarray (FS) and dynamic subarray (DS). Against this background, this paper proposes a machine learning based broadband hybrid precoding for mmWave massive MIMO with DS. Specifically, we first propose an optimal hybrid precoder based on principal component analysis (PCA) for the FS, whereby the frequency-flat RF precoder for each subarray is extracted from the principle component of the optimal frequency-selective precoders for fully-digital MIMO. Moreover, we extend the PCA-based hybrid precoding to DS, where a shared agglomerative hierarchical clustering (AHC) algorithm developed from machine learning is proposed to group the DS for improved spectral efficiency (SE). Finally, we investigate the energy efficiency (EE) of the proposed scheme for both passive and active antennas. Simulations have confirmed that the proposed scheme outperforms conventional schemes in both SE and EE.

cs.IT↗
arXiv2018

Two-Dimensional Multiferroic Semiconductors with Coexisting Ferroelectricity and Ferromagnetism

Low-dimensional multiferroicity, though highly scarce in nature, has attracted great attention due to both fundamental and technological interests. Using first-principles density functional theory, we show that ferromagnetism and ferroelectricity can coexist in monolayer transition metal phosphorus chalcogenides (TMPCs) - CuMP$_2$X$_6$ (M=Cr, V; X=S, Se). These van der Waals layered materials represent a class of 2D multiferroic semiconductors that simultaneously possess ferroelectric and ferromagnetic orders. In these monolayer materials, Cu atoms spontaneously move away from the center atomic plane, giving rise to nontrivial electric dipole moment along the plane normal. In addition, their ferromagnetism originates from indirect exchange interaction between Cr/V atoms, while their out-of-plane ferroelectricity suggests the possibility of controlling electric polarization by external vertical electric field. Monolayer semiconducting TMPCs thus provide a solid-state 2D materials platform for realizing 2D nanoscale switches and memory devices patterned with top and bottom electrodes.

cond-mat.mtrl-sci↗
arXiv2018

Intent Classification using Feature Sets for Domestic Violence Discourse on Social Media

Domestic Violence against women is now recognized to be a serious and widespread problem worldwide. Domestic Violence and Abuse is at the root of so many issues in society and considered as the societal tabooed topic. Fortunately, with the popularity of social media, social welfare communities and victim support groups facilitate the victims to share their abusive stories and allow others to give advice and help victims. Hence, in order to offer the immediate resources for those needs, the specific messages from the victims need to be alarmed from other messages. In this paper, we regard intention mining as a binary classification problem (abuse or advice) with the usecase of abuse discourse. To address this problem, we extract rich feature sets from the raw corpus, using psycholinguistic clues and textual features by term-class interaction method. Machine learning algorithms are used to predict the accuracy of the classifiers between two different feature sets. Our experimental results with high classification accuracy give a promising solution to understand a big social problem through big social media and its use in serving information needs of various community welfare organizations.

cs.CY↗
arXiv2018

Morrey spaces related to certain nonnegative potentials and fractional integrals on the Heisenberg groups

Let $\mathcal L=-Δ_{\mathbb H^n}+V$ be a Schrödinger operator on the Heisenberg group $\mathbb H^n$, where $Δ_{\mathbb H^n}$ is the sub-Laplacian on $\mathbb H^n$ and the nonnegative potential $V$ belongs to the reverse Hölder class $RH_s$ with $s\geq Q/2$. Here $Q=2n+2$ is the homogeneous dimension of $\mathbb H^n$. For given $α\in(0,Q)$, the fractional integrals associated to the Schrödinger operator $\mathcal L$ is defined by $\mathcal I_α={\mathcal L}^{-α/2}$. In this article, we first introduce the Morrey space $L^{p,κ}_{ρ,\infty}(\mathbb H^n)$ and weak Morrey space $WL^{p,κ}_{ρ,\infty}(\mathbb H^n)$ related to the nonnegative potential $V$. Then we establish the boundedness of fractional integrals ${\mathcal L}^{-α/2}$ on these new spaces. Furthermore, in order to deal with certain extreme cases, we also introduce the spaces $\mathrm{BMO}_{ρ,\infty}(\mathbb H^n)$ and $\mathcal{C}^β_{ρ,\infty}(\mathbb H^n)$ with exponent $β\in(0,1]$.

math.CA↗
arXiv2018

Weighted Morrey spaces related to Schrodinger operators with potentials satisfying a reverse Holder inequality and fractional integrals

Let $\mathcal L=-Δ+V$ be a Schrödinger operator on $\mathbb R^d$, $d\geq3$, where $Δ$ is the Laplacian operator on $\mathbb R^d$ and the nonnegative potential $V$ belongs to the reverse Hölder class $RH_s$ for $s\geq d/2$. For given $0<α<d$, the fractional integrals associated to the Schrödinger operator $\mathcal L$ is defined by $\mathcal I_α={\mathcal L}^{-α/2}$.Suppose that $b$ is a locally integrable function on $\mathbb R^d$, the commutator generated by $b$ and $\mathcal I_α$ is defined by $[b,\mathcal I_α]f(x)=b(x)\cdot \mathcal I_αf(x)-\mathcal I_α(bf)(x)$. In this paper, we first introduce some kinds of weighted Morrey spaces related to certain nonnegative potentials belonging to the reverse Hölder class $RH_s$ for $s\geq d/2$. Then we will establish the boundedness properties of the fractional integrals $\mathcal I_α$ on these new spaces. Furthermore, weighted strong-type estimate for the corresponding commutator $[b,\mathcal I_α]$ in the framework of Morrey spaces is also obtained. The classes of weights, the classes of symbol functions as well as weighted Morrey spaces discussed in this paper are larger than $A_{p,q}$, $\mathrm{BMO}(\mathbb R^d)$ and $L^{p,κ}(μ,ν)$ corresponding to the classical case (that is $V\equiv0$).

math.CA↗
arXiv2018

Preserving Patient-centred Controls in Electronic Health Record Systems: A Reliance-based Model Implication

As a consequence of the huge advancement of the Electronic Health Record (EHR) in healthcare settings, the My Health Record (MHR) is introduced in Australia. However security and privacy of the MHR system have been encumbering the development of the system. Even though the MHR system is claimed as patient-cenred and patient-controlled, there are several instances where healthcare providers (other than the usual provider) and system operators who maintain the system can easily access the system and these unauthorised accesses can lead to a breach of the privacy of the patients. This is one of the main concerns of the consumers that affect the uptake of the system. In this paper, we propose a patient centred MHR framework which requests authorisation from the patient to access their sensitive health information. The proposed model increases the involvement and satisfaction of the patients in their healthcare and also suggests mobile security system to give an online permission to access the MHR system.

cs.CY↗
arXiv2018

Scalable Architecture for Personalized Healthcare Service Recommendation using Big Data Lake

The personalized health care service utilizes the relational patient data and big data analytics to tailor the medication recommendations. However, most of the health care data are in unstructured form and it consumes a lot of time and effort to pull them into relational form. This study proposes a novel data lake architecture to reduce the data ingestion time and improve the precision of healthcare analytics. It also removes the data silos and enhances the analytics by allowing the connectivity to the third-party data providers (such as clinical lab results, chemist, insurance company,etc.). The data lake architecture uses the Hadoop Distributed File System (HDFS) to provide the storage for both structured and unstructured data. This study uses K-means clustering algorithm to find the patient clusters with similar health conditions. Subsequently, it employs a support vector machine to find the most successful healthcare recommendations for the each cluster. Our experiment results demonstrate the ability of data lake to reduce the time for ingesting data from various data vendors regardless of its format. Moreover, it is evident that the data lake poses the potential to generate clusters of patients more precisely than the existing approaches. It is obvious that the data lake provides a unified storage location for the data in its native format. It can also improve the personalized healthcare medication recommendations by removing the data silos.

cs.CY↗