arXiv subjects

Ming Zeng

Publications and source records attributed to Ming Zeng.

At least 127 records · Page 7Linked to original sources

arXiv2021

Radiation Reaction of Betatron Oscillation in Plasma Wakefield Accelerators

A classical model of radiation reaction for the betatron oscillation of an electron in a plasma wakefield accelerator is presented. The maximum energy of the electron due to the longitudinal radiation reaction is found, and the betatron oscillation damping due to both the longitudinal and transverse radiation reaction effects is analyzed. Both theoretical and numerical solutions are shown with good agreements. The regime that the quantum radiation takes effect is also discussed. This model is important for designing future plasma based super accelerators or colliders.

physics.plasm-ph↗

arXiv2021

UAV Communications for Sustainable Federated Learning

Federated learning (FL), invented by Google in 2016, has become a hot research trend. However, enabling FL in wireless networks has to overcome the limited battery challenge of mobile users. In this regard, we propose to apply unmanned aerial vehicle (UAV)-empowered wireless power transfer to enable sustainable FL-based wireless networks. The objective is to maximize the UAV transmit power efficiency, via a joint optimization of transmission time and bandwidth allocation, power control, and the UAV placement. Directly solving the formulated problem is challenging, due to the coupling of variables. Hence, we leverage the decomposition technique and a successive convex approximation approach to develop an efficient algorithm, namely UAV for sustainable FL (UAV-SFL). Finally, simulations illustrate the potential of our proposed UAV-SFL approach in providing a sustainable solution for FL-based wireless networks, and in reducing the UAV transmit power by 32.95%, 63.18%, and 78.81% compared with the benchmarks.

cs.NI↗

arXiv2021

IRS-Empowered Wireless Communications: State-of-the-Art, Key Techniques, and Open Issues

In this article, we overview intelligent reflecting surface (IRS)-empowered wireless communication systems. We first present the fundamentals of IRS-assisted wireless transmission. On this basis, we explore the integration of IRS with various advanced transmission technologies, such as millimeter wave, non-orthogonal multiple access, and physical layer security. Following this, we discuss the effects of hardware impairments and imperfect channel-state-information on the IRS system performance. Finally, we highlight several open issues to be addressed.

cs.IT↗

arXiv2021

Modeling the in-orbit background of PolarLight

PolarLight is a gas pixel X-ray polarimeter mounted on a CubeSat, which was launched into a Sun-synchronous orbit in October 2018. We build a mass model of the whole CubeSat with the Geant4 toolkit to simulate the background induced by the cosmic X-ray background (CXB) and high energy charged particles in the orbit. The simulated energy spectra and morphologies of event images both suggest that the measured background with PolarLight is dominated by high energy electrons, with a minor contribution from protons and the CXB. The simulation reveals that, in the energy range of 2-8 keV, there are roughly 28% of the background events are caused by energy deposit from a secondary electron with an energy of a few keV, in a physical process identical to the detection of X-rays. Thus, this fraction of background cannot be discriminated from X-ray events. The background distribution is uneven on the detector plane, with an enhancement near the edges. The edge effect is because high energy electrons tend to produce long tracks, which are discarded by the readout electronics unless they have partial energy deposits near the edges. The internal background rate is expected to be around 6 x 10^-3 counts/s/cm2 in 2-8 keV if an effective particle discrimination algorithm can be applied. This indicates that the internal background should be negligible for future focusing X-ray polarimeters with a focal size in the order of mm.

astro-ph.IM↗

arXiv2021

Ionization-density-dependent Scintillation Pulse Shape and Mechanism of Luminescence Quenching in LaBr3:Ce

Pulse-shape discrimination (PSD) is usually achieved using the different fast and slow decay components of inorganic scintillators, such as BaF2, CsI:Tl, etc. However, LaBr3:Ce is considered to not possess different components at room temperature, but has been proved to have the capability of discriminating γ and α events using fast digitizers. In this paper, ionization-density-dependent transport and rate equations are used to quantitatively model the competing processes in a particle track. With one parameter set, the model reproduces the nonproportionality response of electrons or α particles, and explains the measured α and γ pulse-shape difference well. In particular, the nonlinear quenching of excited dopant ions, Ce3+, is confirmed herein to mainly contribute observable ionization α and γ pulse-shape differences. Further study of the luminescence quenching can also help to better understand the fundamental physics of nonlinear quenching and thus improve the crystal engineering. Moreover, based on the mechanism of dopant quenching, the ionization-density-dependent pulse-shape differences in other fast single-decay-component inorganic scintillators, such as lutetium yttrium oxyorthosilicate, Lu2(1-x)Y2xSiO5:Ce (LYSO) and CeBr3, are also predicted and verified with experiments.

physics.ins-det↗

arXiv2020

Re-detection and a Possible Time Variation of Soft X-ray Polarisation from the Crab

The Crab nebula is so far the only celestial object with a statistically significant detection in soft x-ray polarimetry, a window that has not been explored in astronomy since the 1970s. However, soft x-ray polarimetry is expected to be a sensitive probe of magnetic fields in high energy astrophysical objects including rotation-powered pulsars and pulsar wind nebulae. Here we report the re-detection of soft x-ray polarisation after 40 years from the Crab nebula and pulsar with PolarLight, a miniature polarimeter utilising a novel technique onboard a CubeSat. The polarisation fraction of the Crab in the on-pulse phases was observed to decrease after a glitch of the Crab pulsar on July 23, 2019, while that of the pure nebular emission remained constant within uncertainty. The phenomenon may have lasted about 100 days. If the association between the glitch and polarisation change can be confirmed with future observations, it will place strong constraints on the physical mechanism of the high energy emission and glitch of pulsars.

astro-ph.HE↗

arXiv2020

Robust Design for Intelligent Reflecting Surface Assisted MIMO-OFDMA Terahertz Communications

Recently, terahertz (THz) communication has drawn considerable attention as one of the promising technologies for the future wireless communications owning to its ultra-wide bandwidth. Nonetheless, one major obstacle that prevents the actual deployment of THz lies in its inherent huge attenuation. Intelligent reflecting surface (IRS) and multiple-input multiple-output (MIMO) represent two effective solutions for compensating the large pathloss in THz systems. In this paper, we consider an IRS-aided multi-user THz MIMO system with orthogonal frequency division multiple access, where the sparse radio frequency chain antenna structure is adopted for reducing the power consumption. The objective is to maximize the weighted sum rate via jointly optimizing the hybrid analog/digital beamforming at the base station and reflection matrix at the IRS. {Since the analog beamforming and reflection matrix need to cater all users and subcarriers, it is difficult to directly solve the formulated problem, and thus, an alternatively iterative optimization algorithm is proposed.} Specifically, the analog beamforming is designed by solving a MIMO capacity maximization problem, while the digital beamforming and reflection matrix optimization are both tackled using semidefinite relaxation technique. Considering that obtaining perfect channel state information (CSI) is a challenging task in IRS-based systems, we further explore the case with the imperfect CSI for the channels from the IRS to users. Under this setup, we propose a robust beamforming and reflection matrix design scheme for the originally formulated non-convex optimization problem. Finally, simulation results are presented to demonstrate the effectiveness of the proposed algorithms.

cs.IT↗

arXiv2020

In-orbit Operation and Performance of the CubeSat Soft X-ray Polarimeter PolarLight

PolarLight is a compact soft X-ray polarimeter onboard a CubeSat, which was launched into a low-Earth orbit on October 29, 2018. In March 2019, PolarLight started full operation, and since then, regular observations with the Crab nebula, Sco X-1, and background regions have been conducted. Here we report the operation, calibration, and performance of PolarLight in the orbit. Based on these, we discuss how one can run a low-cost, shared CubeSat for space astronomy, and how CubeSats can play a role in modern space astronomy for technical demonstration, science observations, and student training.

astro-ph.IM↗

arXiv2020

Ponderomotive Injection in Plasma Wakefield Accelerators

A new electron injection scheme is proposed in sub-relativistic plasma wakefield accelerators. A transverse laser ionizes a dopant gas and ponderomotively accelerates the released electrons in the direction of wake propagation. This process enables electron trapping in the wakefield even for a wakefield potential below the trapping threshold. We study the scheme theoretically and by means of particle-in-cell simulations to demonstrate high-quality beam formation and acceleration with sub-micrometer normalized emittances and sub-percent uncorrelated energy spreads.

physics.plasm-ph↗

arXiv2020

Hardware Impaired Ambient Backscatter NOMA Systems: Reliability and Security

Non-orthogonal multiple access (NOMA) and ambient backscatter communication have been envisioned as two promising technologies for the Internet-of-things due to their high spectral efficiency and energy efficiency. Motivated by this fact, we consider an ambient backscatter NOMA system in the presence of a malicious eavesdropper. Under some realistic assumptions of residual hardware impairments (RHIs), channel estimation errors (CEEs) and imperfect successive interference cancellation (ipSIC), we investigate the physical layer security (PLS) of the ambient backscatter NOMA systems focusing on reliability and security. In order to further improve the security of the considered system, an artificial noise scheme is proposed where the radio frequency (RF) source acts as a jammer that transmits interference signal to the legitimate receivers and eavesdropper. On this basis, the analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived. To gain more insights, the asymptotic analysis and diversity orders for the OP in the high signal-to-noise ratio (SNR) regime are carried out, and the asymptotic behaviors of the IP in the high main-to-eavesdropper ratio (MER) region are explored as well. Numerical results show that: 1) RHIs, CEEs and ipSIC have negative effects on the OP but positive effects on the IP; 2) Compared with CEEs, RHIs have a more serious impact on the reliability and security of the considered system; 3) There exists a trade-off between reliability and security, and this trade-off can be optimized by reducing the power coefficient of the artificial noise or increasing the interfering factor of readers; 4) There are error floors for the OP due to the CEEs and the reflection coefficient; 5) As MER grows large, the security for Rnand Rf is improved, while the security for T is reduced.

cs.IT↗

arXiv2020

Controlled density-downramp injection in a beam-driven plasma wakefield accelerator

This paper describes the utilization of beam-driven plasma wakefield acceleration to implement a high-quality plasma cathode via density-downramp injection in a short injector stage at the FLASHForward facility at DESY. Electron beams with charge of up to 105 pC and energy spread of a few percent were accelerated by a tunable effective accelerating field of up to 2.7 GV/m. The plasma cathode was operated drift-free with very high injection efficiency. Sources of jitter, the emittance and divergence of the resulting beam were investigated and modeled, as were strategies for performance improvements that would further increase the wide-ranging applications for a plasma cathode with the demonstrated operational stability

physics.acc-ph↗

arXiv2020

Heatmap-based Vanishing Point boosts Lane Detection

Vision-based lane detection (LD) is a key part of autonomous driving technology, and it is also a challenging problem. As one of the important constraints of scene composition, vanishing point (VP) may provide a useful clue for lane detection. In this paper, we proposed a new multi-task fusion network architecture for high-precision lane detection. Firstly, the ERFNet was used as the backbone to extract the hierarchical features of the road image. Then, the lanes were detected using image segmentation. Finally, combining the output of lane detection and the hierarchical features extracted by the backbone, the lane VP was predicted using heatmap regression. The proposed fusion strategy was tested using the public CULane dataset. The experimental results suggest that the lane detection accuracy of our method outperforms those of state-of-the-art (SOTA) methods.

cs.CV↗

arXiv2020

D-VPnet: A Network for Real-time Dominant Vanishing Point Detection in Natural Scenes

As an important part of linear perspective, vanishing points (VPs) provide useful clues for mapping objects from 2D photos to 3D space. Existing methods are mainly focused on extracting structural features such as lines or contours and then clustering these features to detect VPs. However, these techniques suffer from ambiguous information due to the large number of line segments and contours detected in outdoor environments. In this paper, we present a new convolutional neural network (CNN) to detect dominant VPs in natural scenes, i.e., the Dominant Vanishing Point detection Network (D-VPnet). The key component of our method is the feature line-segment proposal unit (FLPU), which can be directly utilized to predict the location of the dominant VP. Moreover, the model also uses the two main parallel lines as an assistant to determine the position of the dominant VP. The proposed method was tested using a public dataset and a Parallel Line based Vanishing Point (PLVP) dataset. The experimental results suggest that the detection accuracy of our approach outperforms those of state-of-the-art methods under various conditions in real-time, achieving rates of 115fps.

cs.CV↗

arXiv2020

Unstructured Road Vanishing Point Detection Using the Convolutional Neural Network and Heatmap Regression

Unstructured road vanishing point (VP) detection is a challenging problem, especially in the field of autonomous driving. In this paper, we proposed a novel solution combining the convolutional neural network (CNN) and heatmap regression to detect unstructured road VP. The proposed algorithm firstly adopts a lightweight backbone, i.e., depthwise convolution modified HRNet, to extract hierarchical features of the unstructured road image. Then, three advanced strategies, i.e., multi-scale supervised learning, heatmap super-resolution, and coordinate regression techniques are utilized to achieve fast and high-precision unstructured road VP detection. The empirical results on Kong's dataset show that our proposed approach enjoys the highest detection accuracy compared with state-of-the-art methods under various conditions in real-time, achieving the highest speed of 33 fps.

cs.CV↗

arXiv2020

Joint Beamforming And Power Splitting Design For C-RAN With Multicast Fronthaul

In this paper, we investigate the joint beamforming and power splitting design problem in a base station (BS) cluster-based cloud radio access network (C-RAN) with multicast fronthaul, where users are jointly served by BSs within each cluster. Meanwhile, each user can simultaneously obtain information and energy from received signals. On this basis, under predefined minimum harvested energy of each user and maximum transmit power of each BS and central processor, we formulate a sum rate maximization problem by jointly optimizing multicast fronthaul beamforming, cooperative access beamforming and power split ratios. Due to the difficulty in solving the formulated problem, we first transform it into a convex one by successive convex approximate and semidefinite program (SDP) relaxation techniques, and then propose an effective iterative algorithm. Moreover, we design a randomization method that can always obtain the rank-one solution. Finally, numerical results are conducted to validate the effectiveness of our proposed algorithm.

cs.IT↗

arXiv2020

Edge Cache-assisted Secure Low-Latency Millimeter Wave Transmission

In this paper, we consider an edge cache-assisted millimeter wave cloud radio access network (C-RAN). Each remote radio head (RRH) in the C-RAN has a local cache, which can pre-fetch and store the files requested by the actuators. Multiple RRHs form a cluster to cooperatively serve the actuators, which acquire their required files either from the local caches or from the central processor via multicast fronthaul links. For such a scenario, we formulate a beamforming design problem to minimize the secure transmission delay under transmit power constraint of each RRH. Due to the difficulty of directly solving the formulated problem, we divide it into two independent ones: {\textit{i)}} minimizing the fronthaul transmission delay by jointly optimizing the transmit and receive beamforming; {\textit{ii)}} minimizing the maximum access transmission delay by jointly designing cooperative beamforming among RRHs. An alternatively iterative algorithm is proposed to solve the first optimization problem. For the latter, we first design the analog beamforming based on the channel state information of the actuators. Then, with the aid of successive convex approximation and $S$-procedure techniques, a semidefinite program (SDP) is formulated, and an iterative algorithm is proposed through SDP relaxation. Finally, simulation results are provided to verify the performance of the proposed schemes.

cs.IT↗

arXiv2020

Performance of Linear Classification Algorithms on alpha/gamma Discrimination for LaBr3:Ce Scintillation Detectors with Various Pulse Digitizer Properties

With the development of high-speed readout electronics, the digital pulse shape discrimination (PSD) methods have attracted the attention of more researchers, especially in the field of high energy physics and neutron detection. How to choose a PSD algorithm and corresponding data acquisition system (DAQ) naturally becomes a critical problem to settle down for the detection system designers. In this paper, the relationship between the classification performance of different PSD algorithms and digitizers' sampling properties (including sampling rate and the effective number of bits) has been researched based on $\mathrm{LaBr_3}$:Ce scintillation detectors. A self-developed integrated digitizer configured with five different ADCs and a WavePro 404HD oscilloscope were deployed to digitize the waveforms from $\mathrm{LaBr_3}$:Ce scintillators. Moreover, three PSD methods, charge comparison method (CCM), least square for classification method (LS) and Fisher's linear discriminant analysis (LDA), based on linear model were applied to discriminate the alpha signals from the intrinsic isotope $^{227}$Ac. With the LS method and a 125 MSPS 14-Bit ADC, the FoM value was 1.424$\pm$0.042, which is similar to the result from LDA but 31\% better than the result of CCM. The discrimination results showed that the performances of LS and LDA are less affected by the sampling rate with respect to the CCM method, which reflects in a better PSD capability. The results of this paper can help the developers of detector systems to make a trade-off among sampling properties, desirable discrimination results and the cost of systems.

physics.ins-det↗

arXiv2020

Customized Graph Embedding: Tailoring Embedding Vectors to different Applications

Graph is a natural representation of data for a variety of real-word applications, such as knowledge graph mining, social network analysis and biological network comparison. For these applications, graph embedding is crucial as it provides vector representations of the graph. One limitation of existing graph embedding methods is that their embedding optimization procedures are disconnected from the target application. In this paper, we propose a novel approach, namely Customized Graph Embedding (CGE) to tackle this problem. The CGE algorithm learns customized vector representations of graph nodes by differentiating the importance of distinct graph paths automatically for a specific application. Extensive experiments were carried out on a diverse set of node classification datasets, which demonstrate strong performances of CGE and provide deep insights into the model.

cs.LG↗