arXiv subjects

Sheng Yang

Publications and source records attributed to Sheng Yang.

At least 163 records · Page 9Linked to original sources

arXiv2022

Joint Constellation Design for Noncoherent MIMO Multiple-Access Channels

We consider the joint constellation design problem for the noncoherent multiple-input multiple-output multiple-access channel (MAC). By analyzing the noncoherent maximum-likelihood detection error, we propose novel design criteria so as to minimize the error probability. As a baseline approach, we adapt several existing design criteria for the point-to-point channel to the MAC. Furthermore, we propose new design criteria. Our first proposed design metric is the dominating term in nonasymptotic lower and upper bounds on the pairwise error probability exponent. We give a geometric interpretation of the bound using Riemannian distance in the manifold of Hermitian positive definite matrices. From an analysis of this metric at high signal-to-noise ratio, we obtain further simplified metrics. For any given set of constellation sizes, the proposed metrics can be optimized over the set of constellation symbols. Motivated by the simplified metric, we propose a simple constellation construction consisting in partitioning a single-user constellation. We also provide a generalization of our previously proposed construction based on precoding individual constellations of lower dimensions. For a fixed joint constellation, the design metrics can be further optimized over the per-user transmit power, especially when the users transmit at different rates. Considering unitary space-time modulation, we investigate the option of building each individual constellation as a set of truncated unitary matrices scaled by the respective transmit power. Numerical results show that our proposed metrics are meaningful, and can be used as objectives to generate constellations through numerical optimization that perform better, for the same transmission rate and power constraint, than a common pilot-based scheme and the constellations optimized with existing metrics.

cs.IT↗

arXiv2022

An Optimization Framework for General Rate Splitting for General Multicast

Immersive video, such as virtual reality (VR) and multi-view videos, is growing in popularity. Its wireless streaming is an instance of general multicast, extending conventional unicast and multicast, whose effective design is still open. This paper investigates general rate splitting for general multicast. Specifically, we consider a multi-carrier single-cell wireless network where a multi-antenna base station (BS) communicates to multiple single-antenna users via general multicast. We consider linear beamforming at the BS and joint decoding at each user in the slow fading and fast fading scenarios. In the slow fading scenario, we consider the maximization of the weighted sum average rate, which is a challenging nonconvex stochastic problem with numerous variables. To reduce computational complexity, we decouple the original nonconvex stochastic problem into multiple nonconvex deterministic problems, one for each system channel state. Then, we propose an iterative algorithm for each deterministic problem to obtain a Karush-Kuhn-Tucker (KKT) point using the concave-convex procedure (CCCP). In the fast fading scenario, we consider the maximization of the weighted sum ergodic rate. This problem is more challenging than the one for the slow fading scenario, as it is not separable. First, we propose a stochastic iterative algorithm to obtain a KKT point using stochastic successive convex approximation (SSCA) and the exact penalty method. Then, we propose two low-complexity iterative algorithms to obtain feasible points with promising performance for two cases of channel distributions using approximation and CCCP. The proposed optimization framework generalizes the existing ones for rate splitting for various types of services. Finally, we numerically show substantial gains of the proposed solutions over existing schemes in both scenarios.

cs.IT↗

arXiv2022

SN 2019zrk, a bright SN 2009ip analog with a precursor

We present photometric and spectroscopic observations of the Type IIn supernova SN 2019zrk (also known as ZTF20aacbyec). The SN shows a $\gtrsim$ 100 day precursor, with a slow rise, followed by a rapid rise to M $\sim -19.2$ in the $r$ and $g$ bands. The post-peak light-curve decline is well fit with an exponential decay with a timescale of $\sim 39$ days, but it shows prominent undulations, with an amplitude of $\sim 1$ mag. Both the light curve and spectra are dominated by an interaction with a dense circumstellar medium (CSM), probably from previous mass ejections. The spectra evolve from a scattering-dominated Type IIn spectrum to a spectrum with strong P-Cygni absorptions. The expansion velocity is high, $\sim 16,000$ km s$^{-1}$, even in the last spectra. The last spectrum $\sim 110$ days after the main eruption reveals no evidence for advanced nucleosynthesis. From analysis of the spectra and light curves, we estimate the mass-loss rate to be $\sim 4 \times 10^{-2}$ M$_\odot$ yr$^{-1}$ for a CSM velocity of 100 km s$^{-1}$, and a CSM mass of $\gtrsim 1$ M$_\odot$. We find strong similarities for both the precursor, general light curve, and spectral evolution with SN 2009ip and similar SNe, although SN 2019zrk displays a brighter peak magnitude. Different scenarios for the nature of the 09ip-class of SNe, based on pulsational pair instability eruptions, wave heating, and mergers, are discussed. }

astro-ph.HE↗

arXiv2022

Observations of the Very Young Type Ia Supernova 2019np with Early-excess Emission

Early-time radiative signals from type Ia supernovae (SNe Ia) can provide important constraints on the explosion mechanism and the progenitor system. We present observations and analysis of SN 2019np, a nearby SN Ia discovered within 1-2 days after the explosion. Follow-up observations were conducted in optical, ultraviolet, and near-infrared bands, covering the phases from $\sim-$16.7 days to $\sim$+367.8 days relative to its $B-$band peak luminosity. The photometric and spectral evolutions of SN 2019np resembles the average behavior of normal SNe Ia. The absolute B-band peak magnitude and the post-peak decline rate are $M_{\rm max}(B)=-19.52 \pm 0.47$mag and $Δm_{\rm15}(B) =1.04 \pm 0.04$mag, respectively. No Hydrogen line has been detected in the near-infrared and nebular-phase spectra of SN 2019np. Assuming that the $^{56}$Ni powering the light curve is centrally located, we find that the bolometric light curve of SN 2019np shows a flux excess up to 5.0% in the early phase compared to the radiative diffusion model. Such an extra radiation perhaps suggests the presence of an additional energy source beyond the radioactive decay of central nickel. Comparing the observed color evolution with that predicted by different models such as interactions of SN ejecta with circumstellar matter (CSM)/companion star, a double-detonation explosion from a sub-Chandrasekhar mass white dwarf (WD), and surface $^{56}$Ni mixing, the latter one is favored.

astro-ph.HE↗

arXiv2022

Context-Tree-Based Lossy Compression and Its Application to CSI Representation

We propose novel compression algorithms for time-varying channel state information (CSI) in wireless communications. The proposed scheme combines (lossy) vector quantisation and (lossless) compression. First, the new vector quantisation technique is based on a class of parametrised companders applied on each component of the normalised CSI vector. Our algorithm chooses a suitable compander in an intuitively simple way whenever empirical data are available. Then, the sequences of quantisation indices are compressed using a context-tree-based approach. Essentially, we update the estimate of the conditional distribution of the source at each instant and encode the current symbol with the estimated distribution. The algorithms have low complexity, are linear-time in both the spatial dimension and time duration, and can be implemented in an online fashion. We run simulations to demonstrate the effectiveness of the proposed algorithms in such scenarios.

cs.IT↗

arXiv2022

Quasi-periodic oscillations of the X-ray burst from the magnetar SGR J1935+2154 and associated with the fast radio burst FRB 200428

The origin(s) and mechanism(s) of fast radio bursts (FRBs), which are short radio pulses from cosmological distances, have remained a major puzzle since their discovery. We report a strong Quasi-Periodic Oscillation(QPO) of 40 Hz in the X-ray burst from the magnetar SGR J1935+2154 and associated with FRB 200428, significantly detected with the Hard X-ray Modulation Telescope (Insight-HXMT) and also hinted by the Konus-Wind data. QPOs from magnetar bursts have only been rarely detected; our 3.4 sigma (p-value is 2.9e-4) detection of the QPO reported here reveals the strongest QPO signal observed from magnetars (except in some very rare giant flares), making this X-ray burst unique among magnetar bursts. The two X-ray spikes coinciding with the two FRB pulses are also among the peaks of the QPO. Our results suggest that at least some FRBs are related to strong oscillation processes of neutron stars. We also show that we may overestimate the significance of the QPO signal and underestimate the errors of QPO parameters if QPO exists only in a fraction of the time series of a X-ray burst which we use to calculate the Leahy-normalized periodogram.

astro-ph.HE↗

arXiv2022

The Visual-Inertial-Dynamical Multirotor Dataset

Recently, the community has witnessed numerous datasets built for developing and testing state estimators. However, for some applications such as aerial transportation or search-and-rescue, the contact force or other disturbance must be perceived for robust planning and control, which is beyond the capacity of these datasets. This paper introduces a Visual-Inertial-Dynamical (VID) dataset, not only focusing on traditional six degrees of freedom (6-DOF) pose estimation but also providing dynamical characteristics of the flight platform for external force perception or dynamics-aided estimation. The VID dataset contains hardware synchronized imagery and inertial measurements, with accurate ground truth trajectories for evaluating common visual-inertial estimators. Moreover, the proposed dataset highlights rotor speed and motor current measurements, control inputs, and ground truth 6-axis force data to evaluate external force estimation. To the best of our knowledge, the proposed VID dataset is the first public dataset containing visual-inertial and complete dynamical information in the real world for pose and external force evaluation. The dataset: https://github.com/ZJU-FAST-Lab/VID-Dataset and related files: https://github.com/ZJU-FAST-Lab/VID-Flight-Platform are open-sourced.

cs.RO↗

arXiv2022

Infant-phase reddening by surface Fe-peak elements in a normal Type Ia Supernova

Type Ia Supernovae are thermonuclear explosions of white dwarf stars. They play a central role in the chemical evolution of the Universe and are an important measure of cosmological distances. However, outstanding questions remain about their origins. Despite extensive efforts to obtain natal information from their earliest signals, observations have thus far failed to identify how the majority of them explode. Here, we present infant-phase detections of SN 2018aoz from a brightness of -10.5 absolute AB magnitudes -- the lowest luminosity early Type Ia signals ever detected -- revealing a hitherto unseen plateau in the $B$-band that results in a rapid redward color evolution between 1.0 and 12.4 hours after the estimated epoch of first light. The missing $B$-band flux is best-explained by line-blanket absorption from Fe-peak elements in the outer 1% of the ejected mass. The observed $B-V$ color evolution of the SN also matches the prediction from an over-density of Fe-peak elements in the same outer 1% of the ejected mass, whereas bluer colors are expected from a purely monotonic distribution of Fe-peak elements. The presence of excess nucleosynthetic material in the extreme outer layers of the ejecta points to enhanced surface nuclear burning or extended sub-sonic mixing processes in some normal Type Ia Supernova explosions.

astro-ph.HE↗

arXiv2022

Rate Splitting for General Multicast

cs.IT↗

arXiv2021

The In-Flight Realtime Trigger and Localization Software of GECAM

Realtime trigger and localization of bursts are the key functions of GECAM, which is an all-sky gamma-ray monitor launched in Dec 10, 2020. We developed a multifunctional trigger and localization software operating on the CPU of the GECAM electronic box (EBOX). This onboard software has the following features: high trigger efficiency for real celestial bursts with a suppression of false triggers caused by charged particle bursts and background fluctuation, dedicated localization algorithm optimized for short and long bursts respetively, short time latency of the trigger information which is downlinked throught the BeiDou satellite navigation System (BDS). This paper presents the detailed design and deveopment of this trigger and localization software system of GECAM, including the main functions, general design, workflow and algorithms, as well as the verification and demonstration of this software, including the on-ground trigger tests with simulated gamma-ray bursts made by a dedicated X-ray tube and the in-flight performance to real gamma-ray bursts and magnetar bursts.

astro-ph.IM↗

arXiv2021

Gain stabilization and consistency correction approach for multiple SiPM-based gamma-ray detectors on GECAM

Each satellite of the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM, mission) consists of 25 SiPM based gamma-ray detectors (GRDs). Although SiPM based GRD has merits of compact size and low bias-voltage, the drift of the SiPM gain with temperature is a severe problem for GRD performance. An adaptive voltage supply source was designed to automatically adjust the SiPM bias voltage to compensate the temperature effects and keep the gain stable. This approach has been proved to be effective during both the on-ground and in-flight tests. The in-flight measured variation of the SiPM gain is within 2%. To reduce the gain non-uniformity of GRDs, an iterative bias voltage adjustment approach is proposed and implemented. The gain non-uniformity is reduced from 17% to 0.6%. In this paper, the gain stabilization and consistency correction approach are presented and discussed in detail.

physics.ins-det↗

arXiv2021

Progressive Self-Guided Loss for Salient Object Detection

We present a simple yet effective progressive self-guided loss function to facilitate deep learning-based salient object detection (SOD) in images. The saliency maps produced by the most relevant works still suffer from incomplete predictions due to the internal complexity of salient objects. Our proposed progressive self-guided loss simulates a morphological closing operation on the model predictions for progressively creating auxiliary training supervisions to step-wisely guide the training process. We demonstrate that this new loss function can guide the SOD model to highlight more complete salient objects step-by-step and meanwhile help to uncover the spatial dependencies of the salient object pixels in a region growing manner. Moreover, a new feature aggregation module is proposed to capture multi-scale features and aggregate them adaptively by a branch-wise attention mechanism. Benefiting from this module, our SOD framework takes advantage of adaptively aggregated multi-scale features to locate and detect salient objects effectively. Experimental results on several benchmark datasets show that our loss function not only advances the performance of existing SOD models without architecture modification but also helps our proposed framework to achieve state-of-the-art performance.

cs.CV↗

arXiv2021

Adaptive Streaming of 360 Videos with Perfect, Imperfect, and Unknown FoV Viewing Probabilities in Wireless Networks

This paper investigates adaptive streaming of one or multiple tiled 360 videos from a multi-antenna base station (BS) to one or multiple single-antenna users, respectively, in a multi-carrier wireless system. We aim to maximize the video quality while keeping rebuffering time small via encoding rate adaptation at each group of pictures (GOP) and transmission adaptation at each (transmission) slot. To capture the impact of field-of-view (FoV) prediction, we consider three cases of FoV viewing probability distributions, i.e., perfect, imperfect, and unknown FoV viewing probability distributions, and use the average total utility, worst average total utility, and worst total utility as the respective performance metrics. In the single-user scenario, we optimize the encoding rates of the tiles, encoding rates of the FoVs, and transmission beamforming vectors for all subcarriers to maximize the total utility in each case. In the multi-user scenario, we adopt rate splitting with successive decoding and optimize the encoding rates of the tiles, encoding rates of the FoVs, rates of the common and private messages, and transmission beamforming vectors for all subcarriers to maximize the total utility in each case. Then, we separate the challenging optimization problem into multiple tractable problems in each scenario. In the single-user scenario, we obtain a globally optimal solution of each problem using transformation techniques and the Karush-Kuhn-Tucker (KKT) conditions. In the multi-user scenario, we obtain a KKT point of each problem using the concave-convex procedure (CCCP). Finally, numerical results demonstrate that the proposed solutions achieve notable gains over existing schemes in all three cases. To the best of our knowledge, this is the first work revealing the impact of FoV prediction on the performance of adaptive streaming of tiled 360 videos.

cs.MM↗

arXiv2021

Road Mapping and Localization using Sparse Semantic Visual Features

We present a novel method for visual mapping and localization for autonomous vehicles, by extracting, modeling, and optimizing semantic road elements. Specifically, our method integrates cascaded deep models to detect standardized road elements instead of traditional point features, to seek for improved pose accuracy and map representation compactness. To utilize the structural features, we model road lights and signs by their representative deep keypoints for skeleton and boundary, and parameterize lanes via piecewise cubic splines. Based on the road semantic features, we build a complete pipeline for mapping and localization, which includes a) image processing front-end, b) sensor fusion strategies, and c) optimization backend. Experiments on public datasets and our testing platform have demonstrated the effectiveness and advantages of our method by outperforming traditional approaches.

cs.RO↗

arXiv2021

On Linearly Precoded Rate Splitting for Gaussian MIMO Broadcast Channels

In this paper, we consider a general K-user Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). We assume that the channel state is deterministic and known to all the nodes. While the private-message capacity region is well known to be achievable with dirty paper coding (DPC), we are interested in the simpler linearly precoded transmission schemes. In particular, we focus on linear precoding schemes combined with rate-splitting (RS). First, we derive an achievable rate region with minimum mean square error (MMSE) precoding at the transmitter and joint decoding of the sub-messages at the receivers. Then, we study the achievable sum rate of this scheme and obtain two findings: 1) an analytically tractable upper bound on the sum rate that is shown numerically to be a close approximation, and 2) how to reduce the number of active streams -- crucial to the overall complexity -- while preserving the sum rate to within a constant loss. The latter results in two practical algorithms: a stream elimination algorithm and a stream ordering algorithm. Finally, we investigate the constant-gap optimality of linearly precoded RS with respect to the capacity. Our result reveals that, while the achievable rate of linear precoding alone can be arbitrarily far from the capacity, the introduction of RS can help achieve the capacity region to within a constant gap in the two-user case. Nevertheless, we prove that the RS scheme's constant-gap optimality does not extend to the three-user case. Specifically, we show, through a pathological example, that the gap between the sum rate and the sum capacity can be unbounded.

cs.IT↗

arXiv2021

Transmit Correlation Diversity: Generalization, New Techniques, and Improved Bounds

When the users in a MIMO broadcast channel experience different spatial transmit correlation matrices, a class of gains is produced that is denoted transmit correlation diversity. This idea was conceived for channels in which transmit correlation matrices have mutually exclusive eigenspaces, allowing non-interfering training and transmission. This paper broadens the scope of transmit correlation diversity to the case of partially and fully overlapping eigenspaces and introduces techniques to harvest these generalized gains. For the two-user MIMO broadcast channel, we derive achievable degrees of freedom (DoF) and achievable rate regions with/without channel state information at the receiver (CSIR). When CSIR is available, the proposed achievable DoF region is tight in some configurations of the number of receive antennas and the channel correlation ranks. We then extend the DoF results to the $K$-user case by analyzing the interference graph that characterizes the overlapping structure of the eigenspaces. Our achievability results employ a combination of product superposition in the common part of the eigenspaces, and pre-beamforming (rate splitting) to create multiple data streams in non-overlapping parts of the eigenspaces. Massive MIMO is a natural example in which spatially correlated link gains are likely to occur. We study the achievable downlink sum rate for a frequency-division duplex massive MIMO system under transmit correlation diversity.

cs.IT↗

arXiv2021

Learning Image Aesthetic Assessment from Object-level Visual Components

As it is said by Van Gogh, great things are done by a series of small things brought together. Aesthetic experience arises from the aggregation of underlying visual components. However, most existing deep image aesthetic assessment (IAA) methods over-simplify the IAA process by failing to model image aesthetics with clearly-defined visual components as building blocks. As a result, the connection between resulting aesthetic predictions and underlying visual components is mostly invisible and hard to be explicitly controlled, which limits the model in both performance and interpretability. This work aims to model image aesthetics from the level of visual components. Specifically, object-level regions detected by a generic object detector are defined as visual components, namely object-level visual components (OVCs). Then generic features representing OVCs are aggregated for the aesthetic prediction based upon proposed object-level and graph attention mechanisms, which dynamically determines the importance of individual OVCs and relevance between OVC pairs, respectively. Experimental results confirm the superiority of our framework over previous relevant methods in terms of SRCC and PLCC on the aesthetic rating distribution prediction. Besides, quantitative analysis is done towards model interpretation by observing how OVCs contribute to aesthetic predictions, whose results are found to be supported by psychology on aesthetics and photography rules. To the best of our knowledge, this is the first attempt at the interpretation of a deep IAA model.

cs.MM↗

arXiv2021

Magnetar-Driven Shock Breakout Revisited and Implications for Double-Peaked Type I Superluminous Supernovae

The discovery of early bumps in some type-I superluminous supernovae (SLSNe-I) before the main peaks offers an important clue to their energy source mechanisms. In this paper, we updated an analytic magnetar-powered model for fitting the multi-band light curves of double-peaked SLSNe-I: the early bump is powered by magnetar-driven shock breakout thermal emission, and the main peak is powered by a radiative diffusion through the SN ejecta as in the standard magnetar-powered model. Generally, the diffusive luminosity is greater than the shock breakout luminosity at the early time, which makes the shock breakout bumps usually not clearly seen as observed. To obtain a clear double-peaked light curve, inefficient magnetar heating at early times is required. This model is applied to three well-observed double-peaked SLSNe-I (i.e., SN2006oz, LSQ14bdq, and DES14Xtaz). We find that a relative massive SN ejecta with $M_{\mathrm{ej}} \simeq 10.2-18.1 M_{\odot}$ and relative large kinetic energy of SN ejecta $E_{\mathrm{sn}} \simeq (3.8-6.5) \times 10^{51}$ erg are required, and the thermalization efficiency of the magnetar heating is suppressed before $t_{\mathrm{delay}}$, which are in the range of $\simeq 15- 43$ days. The model can well reproduce the observed light curves, with a reasonable and similar set of physical parameters for both the early bump and the main peak, strengthening support for magnetar-powered model. In the future, modeling of the double-peaked SLSNe-I will become more feasible as more events are discovered before the early bump.

astro-ph.HE↗