Xiangming Wen's research while affiliated with Beijing University of Posts and Telecommunications and other places
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Publications (375)
Based on the Richardson and Urbanke (RU) algorithm, the widely used quasi-cyclic low-density parity-check (QC-LDPC) code encodes the parity check matrix (PCM) in blocks, making hardware implementation possible. However, in a QC-LDPC encoding system with multiple expansion factors, storing information bits in excessive register bit widths would redu...
This paper investigates the slice-based service function chain embedding (SBSFCE) problem, which is to embed the service function chains (SFCs) of flows from different slices on a physical network for end-to-end network slice deployment. Compared with regarding slice deployment as complete virtual network embedding (VNE), deploying slices from the...
WiFi signals-based passive gesture tracking is making quick progress in promoting human-computer interaction. The state-of-the-arts have achieved promising cm-level tracking accuracies via the Fresnel ellipses, while they depend heavily on the transceiver positions and the gesture initial positions. This problem is known as the position-dependency...
This paper aims to solve the trajectory tracking control problem for an autonomous vehicle based on reinforcement learning methods. Existing reinforcement learning approaches have found limited successful applications on safety-critical tasks in the real world mainly due to two challenges: 1) sim-to-real transfer; 2) closed-loop stability and safet...
Recently the possibility of forming unmanned aerial vehicle base station (UAV-BS) network systems with energy harvesting capabilities to support persistent wireless access services for pedestrian users has been validated. Due to the need of sustaining wireless access services of the UAV-BSs, we investigate an optimal policy to maximize the overall...
Multi‐agent reinforcement learning has played an increasingly important role in intelligent traffic signal control due to its self‐learning ability. However, existing algorithms only focus on signal timing mechanism design while ignoring the exponential growth of the joint action dimension as the number of intersections increases, which will ultima...
The unmanned aerial vehicles (UAVs) network is vulnerable due to the high mobility and energy-constrained characteristics of UAVs. Nonetheless, as a UAV-based communication network, a stable network topology is crucial for efficient communication. To this end, in this paper, we propose a dynamic weighted clustering algorithm with dual cluster heads...
Gesture awareness plays a crucial role in promoting human-computer interface. Previous works either depend on customized hardware or need a priori learning of wireless signal patterns, facing downsides in terms of the privacy concern, availability and reliability. In this paper, we propose CentiTrack, the first centimeter-level passive gesture trac...
Multicast is an effective transmission mode to support ever-growing multimedia applications. The introduction of software defined networking (SDN) and network function virtualization (NFV) makes the multicast service operation more flexible and efficient. Nevertheless, one main challenge of SDN/NFV-enabled multicast is optimally orchestrating the s...
Detours are inevitable in on-demand customized bus (CB) systems. Previous studies alleviate the impact of detours by predefining high spatial-temporal similarity of travel orders for CB. However, this assumption is clearly inconsistent with orders’ distribution at the urban level and leads to low bus occupancy rate in practical use. In this paper,...
Vehicle time-sensitive communication (VTSC) is an emerging paradigm where the Time-Sensitive Networking together with V2X provides connected vehicle with deterministic and low communication latency. Scheduling is a critical step to realize the determinism. Recently, as the scale and variety of VTSCs increase, the requirements of simultaneously achi...
The development of vehicular intelligence and networking has led to the emergence of vehicular crowdsensing as a new perception paradigm. By integrating edge computing, vehicular intelligence, and Internet of Vehicles technologies, vehicular crowdsensing is poised to have far-reaching implications in the domains of intelligent transportation, indus...
Vehicular crowdsensing has emerged as a prominent sensing paradigm in the Internet of Things (IoT), and its powerful sensing and computing capabilities can provide sufficient data for various applications. To reduce the cost while ensuring the sensing quality, sparse mobile crowdsensing has been proposed, which only requires data from some sensing...
Full frequency reuse combined with precoding is a promising solution for multibeam satellite systems (MSSs) to meet the evergrowing capacity demand. However, line-of-sight-dominant satellite-ground channels will cause severe channel correlation among the geographically clustered hotspot users (HUs), which restricts multiuser capacity over HUs. In t...
During the transition from human-driven vehicles to a fully connected automated vehicle (CAV) traffic environment, the hybrid transportation system in which human-driven vehicles (HDVs) and CAVs coexist will face challenges owing to the uncertainty of HDVs trajectories. Accurately predicting the trajectories of HDVs and conducting safety warnings f...
Vehicular crowdsensing is an efficient method of data collection in cities, benefiting from the powerful moving and sensing capabilities of intelligent vehicles. Modeling sensing capacities of vehicles and analyzing sensing effect based on sensor setup schemes are crucial in vehicular crowdsensing system. If we can infer the sensing strength of veh...
Past few years have witnessed the great potential of exploiting WiFi signals for positioning. Prior work focus on discovering the absolute locations of a radio source, and have achieved promising accuracies of tens of centimeters. However, many applications such as aerial gesture or handwriting tracking are more concerned with the detailed motion s...
The future mobile communication networks (beyond 5th generation (5G)) are evolving toward the service-based architecture where network functions are fine-grained, thereby meeting the dynamic requirements of diverse and differentiated vertical applications. Consequently, the complexity of network management becomes higher, and artificial intelligenc...
This paper addresses high-resolution vehicle positioning and tracking. In recent work, it was shown that a fleet of independent but neighboring vehicles can cooperate for the task of localization by capitalizing on the existence of common surrounding reflectors, using the concept of Team Channel-SLAM. This approach exploits an initial (e.g. GPS-bas...
Satellite communication is becoming an indispensable component of the 5G global networks. Considering the unique characteristics of the satellite communications such as long round trip delay, large cell radius and high satellite speed, initial access and handover are necessary to be improved to guarantee the stable communication for 5G-satellite ne...
![Example of diverse viewpoints included in FERA2017 dataset [35]](publication/352029282/figure/fig5/AS:1157997388664867@1653099500651/Example-of-diverse-viewpoints-included-in-FERA2017-dataset-35_Q320.jpg)
Though the standard convolutional neural networks (CNNs) have been proposed to increase the robustness of facial action unit (AU) detection regarding pose variations, it is hard to enhance detection performance because the standard CNNs are not robust enough to affine transformation. {\color{blue} To address this issue, two novel architectures term...
In view of the rapid development of edge computing and vehicular network, edge-assisted vehicular crowdsensing system has brought significant benefits to Intelligent Transportation Systems (ITS). To satisfy the requirements of ITS applications, a substantial number of sensed data are generated continuously, which incurs considerable communication a...
Orbital angular momentum (OAM) has been a popular topic due to the natural orthogonality of OAM waves with different modes. It is expected to greatly improve the channel capacity of wireless communication systems. From the perspective of networking, this letter proposes an OAM-based different modes networking method (OAM DMN) that sets adjacent cel...
The Internet of Things (IoTs) has become an essential component of the 5th Generation (5G) network and beyond, accelerating the transition to digital society. The increasing signaling traffic generated by billions of IoT devices has placed significant strain on the 5G Core network (5GC) control plane. To address this issue, the 3rd Generation Partn...
Absolute time synchronization is a basic issue in wireless communication. With the advent of 5G, many emerging vertical industry applications have put forward demands for timing accuracy over air interface. High Precision Timing method over Air Interface based on PHY Layer Signals (TAP) is proposed for mobile networks. It is designed to provide mic...
Mobile communication technologies accelerate the development of intelligent transportation by providing connectivity among vehicles and other vehicles, roadside infrastructures, and cloud platforms, thus creating opportunities to achieve carbon neutrality by promoting intelligent shared mobility. Here, we construct a city-level carbon emission mode...
This paper addresses high-resolution vehicle positioning and tracking. In recent work, it was shown that a fleet of independent but neighboring vehicles can cooperate for the task of localization by capitalizing on the existence of common surrounding reflectors, using the concept of Team Channel-SLAM. This approach exploits an initial (e.g. GPS-bas...
The millimeter wave (mmWave) technology enables unmanned aerial vehicles (UAVs) to offer broadband high-speed wireless connectivity in 5G/6G networks. However, the limited footprint of a single UAV implementing analog beamforming (ABF) requires multiple aerial stations to operate in swarms to provide ubiquitous network coverage, thereby posing seri...
Traffic control is regarded as a key issue to alleviate congestion in internet of vehicles (IoV) machine-type communications (MTC). Recently, many traffic control schemes have been studied, such as access class barring (ACB) scheme and back-off (BO) scheme. However, the dynamics of traffic and the heterogeneous requirements of different IoV applica...
Daily activity monitoring is essential to healthy lifestyle assessment and personal healthcare, among which Wi-Fi-based solutions have attracted increasing attention due to their no-intrusive and privacy-protected characters. However, related researches are based on the assumption that there is an interval between two activities, during which the t...
Mobile crowdsensing (MCS) has appeared as a viable solution for data gathering in Internet of Vehicle (IoV). As it utilizes plenty of mobile users to perform sensing tasks, the cost on sensor deployment can be reduced and the data quality can be improved. However, there exist two main challenges for the IoV-based MCS, which are the privacy issues a...
The use of cell-free massive multiple-input multiple-output (MIMO) is regarded as a novel technique in the Industrial Internet of Things (IIoT) networks, and many studies have been reported on its cross-layer optimization including random access and power allocation. Nevertheless, the cooperation of deep reinforcement learning (DRL) and cell-free m...
WiFi-based passive gesture tracking plays a crucial role in promoting human-computer interface, due to its pervasive availability and cost-effectiveness. Prior works focus on tracking gestures on 2D sensing plane by aggregating multiple WiFi links (typically 2), with Uniform Linear Arrays (ULAs). However, gestures actually contain 3D spatial inform...
The continuous development of intelligent traffic control systems has a profound influence on urban traffic planning and traffic management. Indeed, as big data and artificial intelligence continue to evolve, the traffic control strategy based on deep reinforcement learning (RL) has been proven to be a promising method to improve the efficiency of...
Taking advantage of the rich information provided by Wi-Fi measurement setups, Wi-Fi-based human behavior sensing leveraging Channel State Information (CSI) measurements has received a lot of research attention in recent years. The CSI-based human sensing algorithms typically either rely on an explicit channel propagation model or, more recently, a...
The emerging connected and automated vehicle (CAV) has the potential to improve traffic efficiency and safety. With the cooperation between vehicles and intersection, CAVs can adjust speed and form platoons to pass the intersection faster. However, perceptual errors may occur due to external conditions of vehicle sensors. Meanwhile, CAVs and conven...
Edge-assisted vehicular crowdsensing (EAVC) system is an emerging data collection paradigm in Internet of Vehicles (IoV), where intelligent vehicles collaboratively perform complex sensing tasks under the guidance of the edge server. One of the main characteristics of EAVC is that large and balanced spatiotemporal coverage is of paramount importanc...
Re-routing system has become an important technology to improve traffic efficiency. The traditional re-routing schemes do not consider the dynamic characteristics of urban traffic, making the planned routes unable to cope with the changing traffic conditions. Based on real-time traffic information, it is challenging to dynamically re-route connecte...
This paper addresses vehicle positioning, a topic whose importance has risen dramatically in the context of future autonomous driving systems. While classical methods that use GPS and/or beacon signals from network infrastructure for triangulation tend to be sensitive to multi-paths and signal obstruction, our method exhibits robustness with respec...
In this letter, we present Wi-Mose, the first 3D moving human pose estimation system using commodity WiFi. Previous WiFi-based works have achieved 2D and 3D pose estimation. These solutions either capture poses from one perspective or construct poses of people who are at a fixed point, preventing their wide adoption in daily scenarios. To reconstru...
This paper addresses vehicle positioning, a topic whose importance has risen dramatically in the context of future autonomous driving systems. While classical methods that use GPS and/or beacon signals from network infrastructure for triangulation tend to be sensitive to multi-paths and signal obstruction, our method exhibits robustness with respec...
Unmanned aerial vehicles (UAVs) can be utilized to provide communication services for the areas where the communication is unavailable due to the high mobility, agility and low cost. In this letter, we investigate the energy efficient UAVs deployment and the movement for emergency response in the multi-UAVs enabled wireless communication system. Th...
The small, moderate, and large scale saliency patterns in images are valuable to be extracted in saliency detection. By the observation that the probability of small and large saliency patterns appearing in datasets is lower than that of moderate scale saliency patterns. As results, a deep saliency model trained on such datasets would converge to m...
In this paper, we present Wi-Mose, the first 3D moving human pose estimation system using commodity WiFi. Previous WiFi-based works have achieved 2D and 3D pose estimation. These solutions either capture poses from one perspective or construct poses of people who are at a fixed point, preventing their wide adoption in daily scenarios. To reconstruc...
Recently, commodity Wi-Fi devices have been shown to be able to construct human pose images, i.e., human skeletons, as fine-grained as cameras. Existing papers achieve good results when constructing the images of subjects who are in the prior training samples. However, the performance drops when it comes to new subjects, i.e., the subjects who are...