arXiv subjects

Ruibo Wang

Publications and source records attributed to Ruibo Wang.

35 records · Page 2Linked to original sources

arXiv2024

NeRO: Neural Road Surface Reconstruction

Accurately reconstructing road surfaces is pivotal for various applications especially in autonomous driving. This paper introduces a position encoding Multi-Layer Perceptrons (MLPs) framework to reconstruct road surfaces, with input as world coordinates x and y, and output as height, color, and semantic information. The effectiveness of this method is demonstrated through its compatibility with a variety of road height sources like vehicle camera poses, LiDAR point clouds, and SFM point clouds, robust to the semantic noise of images like sparse labels and noise semantic prediction, and fast training speed, which indicates a promising application for rendering road surfaces with semantics, particularly in applications demanding visualization of road surface, 4D labeling, and semantic groupings.

cs.CV↗

arXiv2024

Network-Level Analysis of Integrated Sensing and Communication Using Stochastic Geometry

To meet the demands of densely deploying communication and sensing devices in the next generation of wireless networks, integrated sensing and communication (ISAC) technology is employed to alleviate spectrum scarcity, while stochastic geometry (SG) serves as a tool for low-complexity performance evaluation. To assess network-level performance, there is a natural interaction between ISAC technology and the SG method. From ISAC network perspective, we illustrate how to leverage SG analytical framework to evaluate ISAC network performance by introducing point process distributions and stochastic fading channel models. From SG framework perspective, we summarize the unique performance metrics and research objectives of ISAC networks, thereby extending the scope of SG research in the field of wireless communications. Additionally, considering the limited discussion in the existing SG-based ISAC works in terms of distribution and channel modeling, a case study is designed to exploit topology and channel fading awareness to provide relevant network insights.

cs.NI↗

arXiv2024

Exploring UAV Networking from the Terrain Information Completeness Perspective: A Tutorial

Terrain information is a crucial factor affecting the performance of unmanned aerial vehicle (UAV) networks. As a tutorial, this article provides a unique perspective on the completeness of terrain information, summarizing and enhancing the research on terrain-based UAV deployment. In the presence of complete terrain information, two highly discussed topics are UAV-aided map construction and dynamic trajectory design based on maps. We propose a case study illustrating the mutually reinforcing relationship between them. When terrain information is incomplete, and only terrain-related feature parameters are available, we discuss how existing models map terrain features to blockage probabilities. By introducing the application of this model with stochastic geometry, a case study is proposed to analyze the accuracy of the model. When no terrain information is available, UAVs gather terrain information during the real-time networking process and determine the next position by collected information. This real-time search method is currently limited to relay communication. In the case study, we extend it to a multi-user scenario and summarize three trade-offs of the method. Finally, we conduct a qualitative analysis to assess the impact of three factors that have been overlooked in terrain-based UAV deployment.

cs.NI↗

arXiv2024

Semantic Is Enough: Only Semantic Information For NeRF Reconstruction

Recent research that combines implicit 3D representation with semantic information, like Semantic-NeRF, has proven that NeRF model could perform excellently in rendering 3D structures with semantic labels. This research aims to extend the Semantic Neural Radiance Fields (Semantic-NeRF) model by focusing solely on semantic output and removing the RGB output component. We reformulate the model and its training procedure to leverage only the cross-entropy loss between the model semantic output and the ground truth semantic images, removing the colour data traditionally used in the original Semantic-NeRF approach. We then conduct a series of identical experiments using the original and the modified Semantic-NeRF model. Our primary objective is to obverse the impact of this modification on the model performance by Semantic-NeRF, focusing on tasks such as scene understanding, object detection, and segmentation. The results offer valuable insights into the new way of rendering the scenes and provide an avenue for further research and development in semantic-focused 3D scene understanding.

cs.CV↗

arXiv2023

Ultra Reliable Low Latency Routing in LEO Satellite Constellations: A Stochastic Geometry Approach

In recent years, LEO satellite constellations have become envisioned as a core component of the next-generation wireless communication networks. The successive establishment of mega satellite constellations has triggered further demands for satellite communication advanced features: high reliability and low latency. In this article, we first establish a multi-objective optimization problem that simultaneously maximizes reliability and minimizes latency, then we solve it by two methods. According to the optimal solution, ideal upper bounds for reliability and latency performance of LEO satellite routing can be derived. Next, we design an algorithm for relay satellite subset selection, which can approach the ideal upper bounds in terms of performance. Furthermore, we derive analytical expressions for satellite availability, coverage probability, and latency under the stochastic geometry (SG) framework, and the accuracy is verified by Monte Carlo simulation. In the numerical results, we study the routing performance of three existing mega constellations and the impact of different constellation parameter configurations on performance. By comparing with existing routing strategies, we demonstrate the advantages of our proposed routing strategy and extend the scope of our research.

cs.NI↗

arXiv2023

Terrain-based Coverage Manifold Estimation: Machine Learning, Stochastic Geometry, or Simulation?

Given the necessity of connecting the unconnected, covering blind spots has emerged as a critical task in the next-generation wireless communication network. A direct solution involves obtaining a coverage manifold that visually showcases network coverage performance at each position. Our goal is to devise different methods that minimize the absolute error between the estimated coverage manifold and the actual coverage manifold (referred to as accuracy), while simultaneously maximizing the reduction in computational complexity (measured by computational latency). Simulation is a common method for acquiring coverage manifolds. Although accurate, it is computationally expensive, making it challenging to extend to large-scale networks. In this paper, we expedite traditional simulation methods by introducing a statistical model termed line-of-sight probability-based accelerated simulation. Stochastic geometry is suitable for evaluating the performance of large-scale networks, albeit in a coarse-grained manner. Therefore, we propose a second method wherein a model training approach is applied to the stochastic geometry framework to enhance accuracy and reduce complexity. Additionally, we propose a machine learning-based method that ensures both low complexity and high accuracy, albeit with a significant demand for the size and quality of the dataset. Furthermore, we describe the relationships between these three methods, compare their complexity and accuracy as performance verification, and discuss their application scenarios.

cs.NI↗

arXiv2023

Terrain-Based UAV Deployment: Providing Coverage for Outdoor Users

Deploying unmanned aerial vehicle (UAV) networks to provide coverage for outdoor users has attracted great attention during the last decade. However, outdoor coverage is challenging due to the high mobility of crowds and the diverse terrain configurations causing building blockage. Most studies use stochastic channel models to characterize the impact of building blockage on user performance and do not take into account terrain information. On the other hand, real-time search methods use terrain information, but they are only practical when a single UAV serves a single user.In this paper, we put forward two methods to avoid building blockage in a multi-user system by collecting prior terrain information and using real-time search.We proposed four algorithms related to the combinations of the above methods and their performances are evaluated and compared in different scenarios.By adjusting the height of the UAV based on terrain information collected before networking, the performance is significantly enhanced compared to the one when no terrain information is available.The algorithm based on real-time search further improves the coverage performance by avoiding the shadow of buildings. During the execution of the real-time search algorithm, the search distance is reduced using the collected terrain information.

cs.NI↗

arXiv2023

Reliability Analysis of Multi-hop Routing in Multi-tier LEO Satellite Networks

This article studies the reliability of multi-hop routing in a multi-tier hybrid satellite-terrestrial relay network (HSTRN). We evaluate the reliability of multi-hop routing by introducing interruption probability, which is the probability that no relay device (ground gateway or satellite) is available during a hop. The single-hop interruption probability is derived and extended to the multi-hop interruption probability using a stochastic geometry-based approach. Since the interruption probability in HSTRN highly depends on the priority of selecting communication devices at different tiers, we propose three priority strategies: (i) stationary optimal priority strategy, (ii) single-hop interruption probability inspired strategy, and (iii) density inspired strategy. Among them, the interruption probability under the stationary optimal priority strategy can approach the ideal lower bound. However, when analyzing an HSTRN with a large number of tiers, the stationary optimal priority strategy is computationally expensive. The single-hop interruption probability inspired strategy is expected to be a low-complexity but less reliable alternative to the stationary optimal priority strategy. In numerical results, we study the complementarity between terrestrial devices and satellites. Furthermore, analytical results for reliability are also applicable to the analysis of satellite availability, coverage probability, and ultra-reliable and low latency communications (URLLC) rate. Finally, we extend our original routing strategy into a multi-flow one with dynamic priority strategy.

cs.NI↗

arXiv2023

Resident Population Density-Inspired Deployment of K-tier Aerial Cellular Network

Using unmanned aerial vehicles (UAVs) to enhance network coverage has proven a variety of benefits compared to terrestrial counterparts. One of the commonly used mathematical tools to model the locations of the UAVs is stochastic geometry (SG). However, in the existing studies, both users and UAVs are often modeled as homogeneous point processes. In this paper, we consider an inhomogeneous Poisson point process (PPP)-based model for the locations of the users that captures the degradation in the density of active users as we move away from the town center. In addition, we propose the deployment of aerial vehicles following the same inhomogeneity of the users to maximize the performance. In addition, a multi-tier network model is also considered to make better use of the rich space resources. Then, the analytical expressions of the coverage probability for a typical user and the total coverage probability are derived. Finally, we optimize the coverage probability with limitations of the total number of UAVs and the minimum local coverage probability. Finally we give the optimal UAV distribution parameters when the maximum overall coverage probability is reached.

cs.NI↗

arXiv2022

Programming Bare-Metal Accelerators with Heterogeneous Threading Models: A Case Study of Matrix-3000

As the hardware industry moves towards using specialized heterogeneous many-cores to avoid the effects of the power wall, software developers are finding it hard to deal with the complexity of these systems. This article shares our experience when developing a programming model and its supporting compiler and libraries for Matrix-3000, which is designed for next-generation exascale supercomputers but has a complex memory hierarchy and processor organization. To assist its software development, we developed a software stack from scratch that includes a low-level programming interface and a high-level OpenCL compiler. Our low-level programming model offers native programming support for using the bare-metal accelerators of Matrix-3000, while the high-level model allows programmers to use the OpenCL programming standard. We detail our design choices and highlight the lessons learned from developing systems software to enable the programming of bare-metal accelerators. Our programming models have been deployed to the production environment of an exascale prototype system.

cs.PL↗

arXiv2022

Conditional Contact Angle Distribution in LEO Satellite-Relayed Transmission

This letter characterizes the contact angle distribution based on the condition that the relay low earth orbit (LEO) satellite is in the communication range of both the ground transmitter and the ground receiver. As one of the core distributions in stochastic geometry-based routing analysis, the analytical expression of the \ac{CDF} of the conditional contact angle is derived. Furthermore, the conditional contact angle is applied to analyze the inaccessibility of common satellites between the ground transmitter and receiver. Finally, with the help of the conditional contact angle, coverage probability and achievable data rate in LEO satellite-relayed transmission are studied.

cs.IT↗

arXiv2022

Evaluating the Accuracy of Stochastic Geometry Based Models for LEO Satellite Networks Analysis

This paper investigates the accuracy of recently proposed stochastic geometry-based modeling of low earth orbit (LEO) satellite networks. In particular, we use the Wasserstein Distance-inspired method to analyze the distances between different models, including Fibonacci lattice and orbit models. We propose an algorithm to calculate the distance between the generated point sets. Next, we test the algorithm's performance and analyze the distance between the stochastic geometry model and other more widely acceptable models using numerical results.

cs.NI↗

arXiv2022

Stochastic Geometry-Based Low Latency Routing in Massive LEO Satellite Networks

In this paper, the routing in massive low earth orbit (LEO) satellite networks is studied. When the satellite-to-satellite communication distance is limited, we choose different relay satellites to minimize the latency in a constellation at a constant altitude. Firstly, the global optimum solution is obtained in the ideal scenario when there are available satellites at all the ideal locations. Next, we propose a nearest neighbor search algorithm for realistic (non-ideal) scenarios with a limited number of satellites. The proposed algorithm can approach the global optimum solution under an ideal scenario through a finite number of iterations and a tiny range of searches. Compared with other routing strategies, the proposed algorithm shows significant advantages in terms of latency. Furthermore, we provide two approximation techniques that can give tight lower and upper bounds for the latency of the proposed algorithm, respectively. Finally, the relationships between latency and constellation height, satellites' number, and communication distance are investigated.

cs.NI↗

arXiv2022

A Parallel Direct Eigensolver for Sequences of Hermitian Eigenvalue Problems with No Tridiagonalization

In this paper, a Parallel Direct Eigensolver for Sequences of Hermitian Eigenvalue Problems with no tridiagonalization is proposed, denoted by \texttt{PDESHEP}, and it combines direct methods with iterative methods. \texttt{PDESHEP} first reduces a Hermitian matrix to its banded form, then applies a spectrum slicing algorithm to the banded matrix, and finally computes the eigenvectors of the original matrix via backtransform. Therefore, compared with conventional direct eigensolvers, \texttt{PDESHEP} avoids tridiagonalization, which consists of many memory-bounded operations. In this work, the iterative method in \texttt{PDESHEP} is based on the contour integral method implemented in FEAST. The combination of direct methods with iterative methods for banded matrices requires some efficient data redistribution algorithms both from 2D to 1D and from 1D to 2D data structures. Hence, some two-step data redistribution algorithms are proposed, which can be $10\times$ faster than ScaLAPACK routine \texttt{PXGEMR2D}. For the symmetric self-consistent field (SCF) eigenvalue problems, \texttt{PDESHEP} can be on average $1.25\times$ faster than the state-of-the-art direct solver in ELPA when using $4096$ processes. Numerical results are obtained for dense Hermitian matrices from real applications and large real sparse matrices from the SuiteSparse collection.

math.NA↗

arXiv2021

I-WKNN: Fast-Speed and High-Accuracy WIFI Positioning for Intelligent Stadiums

Based on various existing wireless fingerprint location algorithms in intelligent sports venues, a high-precision and fast indoor location algorithm improved weighted k-nearest neighbor (I-WKNN) is proposed. In order to meet the complex environment of sports venues and the demand of high-speed sampling, this paper proposes an AP selection algorithm for offline and online stages. Based on the characteristics of the signal intensity distribution in intelligent venues, an asymmetric Gaussian filter algorithm is proposed. This paper introduces the application of the positioning algorithm in the intelligent stadium system, and completes the data acquisition and real-time positioning of the stadium. Compared with traditional WKNN and KNN algorithms, the I-WKNN algorithm has advantages in fingerprint positioning database processing, environmental noise adaptability, real-time positioning accuracy and positioning speed, etc. The experimental results show that the I-WKNN algorithm has obvious advantages in positioning accuracy and positioning time in a complex noise environment and has obvious application potential in a smart stadium.

cs.LG↗

arXiv2021

Ultra-Dense LEO Satellite-based Communication Systems: A Novel Modeling Technique

Low earth orbit (LEO) satellite plays an indispensable role in the earth network because of its low latency, large capacity, and seamless global coverage. For such an unprecedented extensive irregular system, stochastic geometry (SG) is a suitable research method. The SG model can not only cope with the increasing network scale but also accurately analyze and estimate the network's performance. Several standard satellite distribution models and satellite-ground channel models are investigated in this paper. System-level metrics such as coverage probability and their intermediates are introduced in the non-technical description. Then, the influence of some factors on latency and coverage probability is studied. Finally, this paper presents the possible challenges and corresponding solutions for the SG-based LEO satellite system analysis.

cs.IT↗

arXiv2019

Lightweight Container-based User Environment

Modern operating systems all support multi-users that users could share a computer simultaneously and not affect each other. However, there are some limitations. For example, privacy problem exists that users are visible to each other in terms of running processes and files. Moreover, users have little freedom to customize the system environment. Last, it is a burden for system administrator to safely manage and update system environment while satisfying multiple users. Facing the above problems, this paper proposes CUE, a Lightweight Container-based User Environment. CUE proposes a new notion that stands in between application container and operating system container:user container. CUE is able to give users more flexibility to customize their environment, achieve privacy isolation, and make system update easier and safer. Its goal is to optimize and enhance the multi-user notion of current operating system and being lightweight. Moreover, it is able to facilitate application deployment in high performance clusters. It is currently deployed in NUDT's Tianhe E prototype supercomputer. Experiment results show that it introduces negligible overhead.

cs.DC↗