arXiv subjects

Jing Yang

Publications and source records attributed to Jing Yang.

At least 415 records · Page 23Linked to original sources

arXiv2018

Riding on the Primary: A New Spectrum Sharing Paradigm for Wireless-Powered IoT Devices

In this paper, a new spectrum sharing model referred to as riding on the primary (ROP) is proposed for wireless-powered IoT devices with ambient backscatter communication capabilities. The key idea of ROP is that the secondary transmitter harvests energy from the primary signal, then modulates its information bits to the primary signal, and reflects the modulated signal to the secondary receiver without violating the primary system's interference requirement. Compared with the conventional spectrum sharing model, the secondary system in the proposed ROP not only utilizes the spectrum of the primary system but also takes advantage of the primary signal to harvest energy and to carry its information. In this paper, we investigate the performance of such a spectrum sharing system under fading channels. To be specific, we maximize the ergodic capacity of the secondary system by jointly optimizing the transmit power of the primary signal and the reflection coefficient of the secondary ambient backscatter. Different (ideal/practical) energy consumption models, different (peak/average) transmit power constraints, different types (fixed/dynamically adjustable) reflection coefficient, different primary system's interference requirements (rate/outage) are considered. Optimal power allocation and reflection coefficient are obtained for each scenario.

cs.IT↗

arXiv2018

Sending Information Through Status Updates

We consider an energy harvesting transmitter sending status updates regarding a physical phenomenon it observes to a receiver. Different from the existing literature, we consider a scenario where the status updates carry information about an independent message. The transmitter encodes this message into the timings of the status updates. The receiver needs to extract this encoded information, as well as update the status of the observed phenomenon. The timings of the status updates, therefore, determine both the age of information (AoI) and the message rate (rate). We study the tradeoff between the achievable message rate and the achievable average AoI. We propose several achievable schemes and compare their rate-AoI performances.

cs.IT↗

arXiv2017

Omnidirectional Ventilated Acoustic Barrier

As an important problem in acoustics, sound insulation finds applications in a great variety of situations. In the existing schemes, however, there has always been a tradeoff between the thinness of sound-insulating devices and their ventilating capabilities, limiting their potentials in the control of low-frequency sound in high ventilation environments. Here we design and experimentally implement an omnidirectional acoustic barrier with planar profile, subwavelength thickness (0.18lambda) yet high ventilation. The proposed mechanism is based on the interference between the resonant scattering of discrete states and the background scattering of continuous states that induces Fano-like asymmetric transmission profile. Benefitting from the binarystructured design of coiled unit and hollow pipe, it maximally simplifies the design and fabrication while ensuring the ventilation for all the non resonant units with open tubes. The simulated and measured results agree well, showing the effectiveness of our proposed mechanism to block low frequency sound coming from various directions while allowing 63% of the air flow to pass. We anticipate our design to open routes to design sound insulators and to enable applications in traditionally unattainable cases such as those calling for noise reduction and cooling simultaneously.

physics.app-ph↗

arXiv2017

Giant Thermal Conductivity Enhancement in Multilayer MoS2 under Highly Compressive Strain

Multilayer MoS2 possesses highly anisotropic thermal conductivities along in-plane and cross-plane directions that could hamper heat dissipation in electronics. With about 9% cross-plane compressive strain created by hydrostatic pressure in a diamond anvil cell, we observed about 12 times increase in the cross-plane thermal conductivity of multilayer MoS2. Our experimental and theoretical studies reveal that this drastic change arises from the greatly strengthened interlayer interaction and heavily modified phonon dispersions along cross-plane direction, with negligible contribution from electronic thermal conductivity, despite its enhancement of 4 orders of magnitude. The anisotropic thermal conductivity in the multilayer MoS2 at ambient environment becomes almost isotropic under highly compressive strain, effectively transitioning from 2D to 3D heat dissipation. This strain tuning approach also makes possible parallel tuning of structural, thermal and electrical properties, and can be extended to the whole family of 2D Van der Waals solids, down to two layer systems.

cond-mat.mtrl-sci↗

arXiv2017

Hybrid functional pseudopotentials

The consistency between the exchange-correlation functional used in pseudopotential construction and in the actual density functional theory calculation is essential for the accurate prediction of fundamental properties of materials. However, routine hybrid density functional calculations at present still rely on GGA pseudopotentials due to the lack of hybrid functional pseudopotentials. Here, we present a scheme for generating hybrid functional pseudopotentials, and we analyze the importance of pseudopotential density functional consistency for hybrid functionals. We benchmark our PBE0 pseudopotentials for structural parameters and fundamental electronic gaps of the G2 molecular dataset and some simple solids. Our results show that using our new PBE0 pseudopotentials in PBE0 calculations improves agreement with respect to all-electron calculations.

physics.chem-ph↗

arXiv2017

Tribopolymer Formation Mechanism on the RuO$_2$(110) Surface

Tribopolymer formed on the contacts of microelectromechanical and nanoelectromechanical system (MEMS/NEMS) devices is a major concern hampering their practical use in information technology. Conductive metal oxides, such as RuO$_2$ and ReO$_3$, have been regarded as promising candidate materials for MEMS/NEMS contacts due to their conductivity, hardness, and relatively chemically inert surfaces. However, recent experimental works demonstrate that trace amounts of polymer could still form on RuO$_2$ surfaces. In this study, we demonstrate the mechanism of this class of unexpected tribopolymer formation by conducting density functional theory based computational compression experiments with benzene as the contamination gas. First, mechanical force during compression changes the benzene molecules from slightly physisorbed to strongly chemisorbed. Further compression causes deformation and chemical linkage of the benzene molecules. Finally, the two contacts detach, with one having a complex organic molecule attached and the other with a more reactive surface. The complex organic molecule, which has an oxabicyclic segment, can be viewed as the rudiment of tribopolymer, and the more reactive surface can trigger the next adsorption--reaction--tribopolymer formation cycle. Based on these results, we also predict tribopolymer formation rates by using transition--state theory and the second--order rate law. This study deepens our understanding of tribopolymer formation (especially on metal oxides) and provides strategies for suppressing tribopolymerization.

cond-mat.mtrl-sci↗

arXiv2017

Pion transverse-momentum spectrum, elliptic flow, and Hanbury-Brown-Twiss interferometry in a viscous granular source model

We examine the evolution of quark-gluon plasma (QGP) droplets with viscous hydrodynamics and analyze the pion transverse-momentum spectrum, elliptic flow, and Hanbury-Brown-Twiss (HBT) interferometry in a granular source model consisting of viscous QGP droplets. The shear viscosity of the QGP droplet speeds up and slows down the droplet evolution in the central and peripheral regions of the droplet, respectively. The effect of the bulk viscosity on the evolution is negligible. Although there are viscous effects on the droplet evolution, the pion momentum spectrum and elliptic flow change little for granular sources with and without viscosity. On the other hand, the influence of viscosity on HBT radius $R_{\rm out}$ is considerable. It makes $R_{\rm out}$ decrease in the granular source model. We determine the model parameters of granular sources using the experimental data of pion transverse-momentum spectrum, elliptic flow, and HBT radii together, and investigate the effects of viscosity on the model parameters. The results indicate that the granular source model may reproduce the experimental data of pion transverse-momentum spectrum, elliptic flow, and HBT radii in heavy-ion collisions of Au-Au at $\sqrt{s_{NN}}=200$ GeV and Pb-Pb at $\sqrt{s_{NN}}=2.76$ TeV in different centrality intervals. The viscosity of the droplet leads to an increase in the initial droplet radius and a decrease of the source shell parameter in the granular source model.

nucl-th↗

arXiv2017

Multiplicities of Character Values of Binary Sidel'nikov-Lempel-Cohn-Eastman Sequences

Binary Sidel'nikov-Lempel-Cohn-Eastman sequences (or SLCE sequences) over F 2 have even period and almost perfect autocorrelation. However, the evaluation of the linear complexity of these sequences is really difficult. In this paper, we continue the study of [1]. We first express the multiple roots of character polynomials of SLCE sequences into certain kinds of Jacobi sums. Then by making use of Gauss sums and Jacobi sums in the "semiprimitive" case, we derive new divisibility results for SLCE sequences.

cs.IT↗

arXiv2017

Energy Efficiency Challenges of 5G Small Cell Networks

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this paper is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell BS's. Moreover, the computation power of 5G small cell BS can approach 800 watt when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks.

cs.NI↗

arXiv2016

Learning the Interference Graph of a Wireless Network

A key challenge in wireless networking is the management of interference between transmissions. Identifying which transmitters interfere with each other is a crucial first step. In this paper we cast the task of estimating the a wireless interference environment as a graph learning problem. Nodes represent transmitters and edges represent the presence of interference between pairs of transmitters. We passively observe network traffic transmission patterns and collect information on transmission successes and failures. We establish bounds on the number of observations (each a snapshot of a network traffic pattern) required to identify the interference graph reliably with high probability. Our main results are scaling laws that tell us how the number of observations must grow in terms of the total number of nodes $n$ in the network and the maximum number of interfering transmitters $d$ per node (maximum node degree). The effects of hidden terminal interference (i.e., interference not detectable via carrier sensing) on the observation requirements are also quantified. We show that to identify the graph it is necessary and sufficient that the observation period grows like $d^2 \log n$, and we propose a practical algorithm that reliably identifies the graph from this length of observation. The observation requirements scale quite mildly with network size, and networks with sparse interference (small $d$) can be identified more rapidly. Computational experiments based on a realistic simulations of the traffic and protocol lend additional support to these conclusions.

cs.IT↗

arXiv2016

Adsorption of Benzene on the RuO2(110) Surface

Hydrocarbon tribopolymer, a type of polymer formed due to friction between surfaces, is a major impediment to the development of micro- and nanoelectromechanical systems (MEMS/NEMS) devices for industrial application. Tribopolymer buildup can prevent MEMS and NEMS from making or breaking electrical contact. We describe the adsorption of benzene (C6H6) on the RuO2(110) surface using density functional theory. This adsorption is an important initial step in the mechanism of hydrocarbon tribopolymer layer formation on MEMS and NEMS devices. The adsorption interaction is studied by considering three oxygen coverages of RuO2(110) and all the possible adsorption sites for benzene. We find that adsorption of benzene on O-poor RuO2(110) via C-Ru bonds is stronger than adsorption on the O-rich RuO2(110) via H-O bonds. For an in-depth study of the adsorption behavior, we include the van der Waals interaction for a holistic investigation. By incorporating the thermodynamic chemical potentials into the adsorption simulations, we describe a model that can provide guidance for realistic situations.

cond-mat.mtrl-sci↗

arXiv2016

Quantum parameter estimation with the Landau-Zener transition

We investigate the fundamental limits in precision allowed by quantum mechanics from Landau-Zener transitions, concerning Hamiltonian parameters. While the Landau-Zener transition probabilities depend sensitively on the system parameters, much more precision may be obtained using the acquired phase, quantified by the quantum Fisher information. This information scales with a power of the elapsed time for the quantum case, whereas it is time-independent if the transition probabilities alone are used. We add coherent control to the system, and increase the permitted maximum precision in this time-dependent quantum system. The case of multiple passes before measurement, "Landau-Zener-Stueckelberg interferometry", is considered, and we demonstrate that proper quantum control can cause the quantum Fisher information about the oscillation frequency to scale as $T^4$, where $T$ is the elapsed time.

quant-ph↗

arXiv2016

Fog Data: Enhancing Telehealth Big Data Through Fog Computing

The size of multi-modal, heterogeneous data collected through various sensors is growing exponentially. It demands intelligent data reduction, data mining and analytics at edge devices. Data compression can reduce the network bandwidth and transmission power consumed by edge devices. This paper proposes, validates and evaluates Fog Data, a service-oriented architecture for Fog computing. The center piece of the proposed architecture is a low power embedded computer that carries out data mining and data analytics on raw data collected from various wearable sensors used for telehealth applications. The embedded computer collects the sensed data as time series, analyzes it, and finds similar patterns present. Patterns are stored, and unique patterns are transmited. Also, the embedded computer extracts clinically relevant information that is sent to the cloud. A working prototype of the proposed architecture was built and used to carry out case studies on telehealth big data applications. Specifically, our case studies used the data from the sensors worn by patients with either speech motor disorders or cardiovascular problems. We implemented and evaluated both generic and application specific data mining techniques to show orders of magnitude data reduction and hence transmission power savings. Quantitative evaluations were conducted for comparing various data mining techniques and standard data compression techniques. The obtained results showed substantial improvement in system efficiency using the Fog Data architecture.

cs.CY↗

arXiv2016

Non-Hermitian acoustic metamaterial for the complete control of sound by accessing the exceptional points

Non-Hermitian systems always play a negative role in wave manipulations due to inherent non-conservation of energy as well as loss of information. Recently, however, there has been a paradigm shift on utilizing non-Hermitian systems to implement varied miraculous wave controlling. For example, parity-time symmetric media with well-designed loss and gain are presented to create a nontrivial effect of unidirectional diffraction, which is observed near the exceptional points (EPs) in the non-Hermitian systems. Here, we report the design and realization of non-Hermitian acoustic metamaterial (NHAM) and show that by judiciously tailoring the inherent loss, the phase and amplitude of reflection can possibly be tuned in a decoupled manner. Such decoupled tuning of phase and amplitude is closely related to the EPs. As a demonstration of functionality, we experimentally generate a high-quality acoustic hologram via NHAM. Our work may open a new degree of freedom for realizing the complete control of sound.

physics.class-ph↗

arXiv2016

Non-Asymptotic Achievable Rates for Energy-Harvesting Channels using Save-and-Transmit

This paper investigates the information-theoretic limits of energy-harvesting (EH) channels in the finite blocklength regime. The EH process is characterized by a sequence of i.i.d. random variables with finite variances. We use the save-and-transmit strategy proposed by Ozel and Ulukus (2012) together with Shannon's non-asymptotic achievability bound to obtain lower bounds on the achievable rates for both additive white Gaussian noise channels and discrete memoryless channels under EH constraints. The first-order terms of the lower bounds of the achievable rates are equal to $C$ and the second-order (backoff from capacity) terms are proportional to $-\sqrt{ \frac{\log n}{n}}$, where $n$ denotes the blocklength and $C$ denotes the capacity of the EH channel, which is the same as the capacity without the EH constraints. The constant of proportionality of the backoff term is found and qualitative interpretations are provided.

cs.IT↗

arXiv2016

Origin of the superconductivity of WTe2 under pressure

Tungsten ditelluride (WTe2) has attracted significant attention due to its interesting electronic properties, such as the unsaturated magnetoresistance and superconductivity. Recently, it has been proposed to be a new type of Weyl semimetal, which is distinguished from other transition metal dichalcogenides (TMDs) from a topological prospective. Here, we study the structure of WTe2 under pressure with a crystal structure prediction and ab initio calculations combined with high pressure synchrotron X-ray diffraction and Raman spectroscopy measurements. We find that the ambient orthorhombic structure (Td) transforms into a monoclinic structure (1T') at around 4-5 GPa. As the transition pressure is very close to the critical point in recent high-pressure electrical transport measurements, the emergence of superconductivity in WTe2 under pressure is attributed to the Td-1T' structure phase transition, which associates with a sliding mechanism of the TMD layers and results in a shorter Te-Te interlayer distance compared to the intralayer ones. These results highlight the critical role of the interlayer stacking and chalcogen interactions on the electronic and superconducting properties of multilayered TMDs under hydrostatic strain environments.

cond-mat.mtrl-sci↗

arXiv2016

Inferring the perturbation time from biological time course data

Time course data are often used to study the changes to a biological process after perturbation. Statistical methods have been developed to determine whether such a perturbation induces changes over time, e.g. comparing a perturbed and unperturbed time course dataset to uncover differences. However, existing methods do not provide a principled statistical approach to identify the specific time when the two time course datasets first begin to diverge after a perturbation; we call this the perturbation time. Estimation of the perturbation time for different variables in a biological process allows us to identify the sequence of events following a perturbation and therefore provides valuable insights into likely causal relationships. In this paper, we propose a Bayesian method to infer the perturbation time given time course data from a wild-type and perturbed system. We use a non-parametric approach based on Gaussian Process regression. We derive a probabilistic model of noise-corrupted and replicated time course data coming from the same profile before the perturbation time and diverging after the perturbation time. The likelihood function can be worked out exactly for this model and the posterior distribution of the perturbation time is obtained by a simple histogram approach, without recourse to complex approximate inference algorithms. We validate the method on simulated data and apply it to study the transcriptional change occurring in Arabidopsis following inoculation with P. syringae pv. tomato DC3000 versus the disarmed strain DC3000hrpA. An R package, DEtime, implementing the method is available at https://github.com/ManchesterBioinference/DEtime along with the data and code required to reproduce all the results.

q-bio.QM↗

arXiv2016

Quickest Change Detection with Mismatched Post-Change Models

In this paper, we study the quickest change detection with mismatched post-change models. A change point is the time instant at which the distribution of a random process changes. The objective of quickest change detection is to minimize the detection delay of an unknown change point under certain performance constraints, such as average run length (ARL) to false alarm or probability of false alarm (PFA). Most existing change detection procedures assume perfect knowledge of the random process distributions before and after the change point. However, in many practical applications such as anomaly detection, the post-change distribution is often unknown and needs to be estimated with a limited number of samples. In this paper, we study the case that there is a mismatch between the true post-change distribution and the one used during detection. We analytically identify the impacts of mismatched post-change models on two classical detection procedures, the cumulative sum (CUSUM) procedure and the Shiryaev-Roberts (SR) procedure. The impacts of mismatched models are characterized in terms of various finite or asymptotic performance bounds on ARL, PFA, and average detection delay (ADD). It is shown that post-change model mismatch results in an increase in ADD, and the rate of performance degradation depends on the difference between two Kullback-Leibler (KL) divergences, one is between the priori- and post-change distributions, and the other one is between the true and mismatched post-change distributions.

stat.ME↗