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A Multi-Objective Optimization Approach for Roadside Unit Deployment Strategy in IoV

A Multi-Objective Optimization Approach for Roadside Unit De...

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IEEE Conference on Wireless Communications and networking

作者： Meihan Lin Jie Huo Luhan Wang Guanyu Yao Yawen Chen Zhaoming Lu Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Roadside unit (RSU) deployment plays a crucial role in enhancing the quality of service (QoS) in Vehicular Ad-hoc networks (VANET). To determine the optimal quantities and locations of deployed RSUs for maximum effectiveness, previous research categorized this as a single-objective optimization problem, considering only the performance indicators for vehicle-to-infrastructure (V2I) communication and solving it using heuristic algorithms or learning-based algorithms. Nonetheless, in the event of information interaction among RSUs as a supplementary component to V2I communication, the process of data transmission and dissemination will achieve a heightened level of comprehensiveness and efficiency within the network. In this paper, we construct a multi-objective roadside unit deployment model (MORD) that takes both V2I communication and data interaction between RSUs into account. The optimization problem of MORD is solved by a multi-objective evolutionary algorithm. We perform a series of simulation evaluations in the ideal grid scenario and the real road network scenario. The results prove that compared to other schemes, the proposed algorithm can better balance the relationship between various objectives in MORD. Moreover, the algorithm can provide decision makers with non-dominated solution sets to choose an appropriate deployment scheme that is more suitable for the actual conditions.

关键词： Wireless communication Heuristic algorithms Vehicle-to-infrastructure Roads Vehicular ad hoc networks Quality of service Transforms

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Scalable and Efficient URLLC Resource Allocation Based on Offline Graph Reinforcement Learning

Scalable and Efficient URLLC Resource Allocation Based on Of...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Ren Jiaqi Wenpeng Jing Xiangming Wen Zhaoming Lu Shuyue Zhao Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China

Deep reinforcement learning (RL) has emerged as a transformative technology for addressing intricate radio resource allocation problems in both 5G and 6G networks. Nevertheless, during the training phases of RL-based resource allocation algorithms, online RL methods introduce potential risks as they necessitate continuous interaction with the environment. Motivated by the fact that the historical data of the resource allocation process in the base station (BS) reveals the operation rules of the mobile network dynamics, this paper proposes a novel data-driven framework for resource allocation optimization, termed Offline Graph Reinforcement Learning (OGRL). Different from existing intelligent resource allocation schemes, which acquire policies by interacting either with wireless network simulators or real-world networks, the proposed OGRL framework exclusively leverages historical data from BS to train a high-performance resource allocation policy. Furthermore, by harnessing the capabilities of the graph neural networks (GNNs) at processing intricate data structures, OGRL can adeptly manage dynamic network environments characterized by continuously changing active users. Extensive experimental results substantiate that, following training with historical data, the proposed OGRL attains Quality of Service (QoS) and packet loss rates comparable to those of the best online algorithms. Furthermore, OGRL exhibits excellent scalability and generalization capabilities.

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Video-Based Multi-Stage 3D Human Mesh Reconstruction

Video-Based Multi-Stage 3D Human Mesh Reconstruction

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International Conference on Computer and Communications (ICCC)

作者： Zhiwen Qiu Muqing Wu Qihui Su Chengzhang Yin Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

Existing Model-based 3D human reconstruction provides a new perspective for generating realistic full-body meshes for 3D human pose estimation. However, many existing methods for reconstructing human meshes typically rely on neural networks to directly estimate the parameters of the SMPL model, subsequently utilizing the SMPL model to recover the human mesh. Despite significant progress in recent research, these methods still encounter several issues, including shape estimation overfitting, cumulative rotation errors, and rotational semantic ambiguities. Furthermore, these methods have not leveraged recent advancements in 2D and 3D pose estimation. To address these challenges, we propose a framework that decomposes the task of reconstructing 3D human meshes into three components: extracting 2D keypoints, a 2D-to-3D lifting network, and fitting the rotations of the keypoints. We decompose the rotation of the 3D keypoints into twist and swing components. In the 2D-to-3D network, we regress the 3D keypoint locations, shape parameters, and twist of the keypoints, while also introducing an optimization method for fitting the rotations. We conducted experiments on the Human3.6M dataset, achieving significant performance improvements.

关键词： Solid modeling Three-dimensional displays Shape Pose estimation Pipelines Neural networks Fitting Semantics Bones Overfitting

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Sum-Rate Maximization for Active RIS-Aided Downlink RSMA system

Sum-Rate Maximization for Active RIS-Aided Downlink RSMA Sys...

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2023 IEEE INFOCOM Conference on Computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Li, Xinhao Wang, Tao Tong, Haonan Yang, Zhaohui Mao, Yijie Yin, Changchuan Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China School of Information Science and Technology ShanghaiTech University Shanghai China

ISBN: (纸本)9781665494274

In this paper, the problem of sum-rate maximization for an active reconfigurable intelligent surface (RIS) assisted downlink rate-splitting multiple access (RSMA) transmission system is studied. In the considered model, the active RIS is deployed to overcome severe power attenuation, which is caused by the cumulative product of RIS incidence path loss and the reflection path loss. Since the active RIS can adjust both the phase and the amplitude of the incident signal simultaneously, the RIS control scheme requires delicate design to improve RSMA communication performance. To address this issue, a sum-rate maximization problem is formulated to jointly optimize the beamforming vectors, rate allocation vector, and RIS precoding matrix. To solve this non-convex sum-rate maximization problem, an iterative algorithm based on fractional programming (FP) and quadratic constraint quadratic programming (QCQP) is proposed. In particular, the proposed algorithm firstly decomposes the original problem into two subproblems, namely, 1) beamforming and rate allocation optimization and 2) active RIS precoding optimization. The corresponding variables of the two subproblems are optimized through sequential convex approximation (SCA) and block coordinate descent (BCD), respectively. Numerical results show that the proposed active RIS-aided RSMA system could increase the sum-rate by up to 45% over the conventional passive RIS-aided RSMA system with the same energy consumption. © 2023 IEEE.

关键词： Iterative methods

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Two-Stage DoA Estimation for ISAC system Based on a MIMO OFDM Radar

Two-Stage DoA Estimation for ISAC System Based on a MIMO OFD...

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Radio Frequency and Antenna Technologies (iWRF&AT), IEEE International Workshop on

作者： Zhengyu Huang Danpu Liu Zhilong Zhang Beijing Laboratory of Advanced Information Network Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications P.R. China Beijing China

ISBN: (数字)9798350384765

ISBN: (纸本)9798350384772

In the next generation of communication networks, mobile networks and widely deployed based stations will achieve statisfactory integrated sensing and communication (ISAC) functions under the standard multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) architecture and waveform. In this paper, we focuse on an ISAC system based on a MIMO OFDM radar and propose a Two-Stage mutiple signal Classification (MUSIC) direction of arrival (DoA) estimation algorithm. In order to achieve a precise estimation while maintaining low computational cost, an estimate on the direction of the user is roughly obtained in the first stage, and then refined in the second stage. Compared with traditional DoA estimation algorithms including MUSIC and discrete fourier transform-compressed sensing, the root mean square error (RMSE) for multi-target DoA estimation can be reduced by two orders of mangnitude under the same computational cost.

关键词： Direction-of-arrival estimation Transmitters OFDM Estimation Pattern classification Radar Integrated sensing and communication

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Sparsely Deployed Bluetooth and Magnetic Fusion Positioning for Large Underground Parking Lots

Sparsely Deployed Bluetooth and Magnetic Fusion Positioning ...

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IEEE Conference on Wireless Communications and networking

作者： Ziwen Luo Yihong Zheng Shuya Zhou Shumin Wang Xinghe Chu Luhan Wang Zhaoming Lu Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

The global navigation satellite system (GNSS) fails in indoor environments, leading to a growing demand for indoor positioning, ranging from above-ground buildings to under-ground parking lots. Existing indoor positioning technologies face challenges balancing low cost, low latency, and high accuracy, particularly in large underground parking lots (LUPLs). This paper proposes a sparsely deployed Bluetooth and magnetic (SBM) fusion positioning system for LUPL scenarios. Specifically, the spatial characteristics of the received signal strength indicator (RSSI) from sparsely deployed Bluetooth and the magnetic field strength are analyzed. Static and dynamic algorithms are designed for the SBM system by utilizing Bluetooth's area division and coarse positioning, combined with the high precision of magnetic field positioning. Experimental results from a real LUPL deployment demonstrate that, under a sparse beacon distribution (1 beacon per 294 m 2 ), the proposed positioning algorithms achieve static accuracy of 1.32 m, dynamic accuracy of 0.75 m, and low latency on consumer-grade devices.

关键词： Global navigation satellite system Bluetooth Accuracy Costs Heuristic algorithms Magnetic fields Received signal strength indicator Vehicle dynamics Low latency communication Smart phones

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Sparsely Deployed Bluetooth and Magnetic Fusion Positioning for Large Underground Parking Lots

Sparsely Deployed Bluetooth and Magnetic Fusion Positioning ...

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2025 IEEE Wireless Communications and networking Conference, WCNC 2025

作者： Luo, Ziwen Zheng, Yihong Zhou, Shuya Wang, Shumin Chu, Xinghe Wang, Luhan Lu, Zhaoming Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798350368369

The global navigation satellite system (GNSS) fails in indoor environments, leading to a growing demand for indoor positioning, ranging from above-ground buildings to under-ground parking lots. Existing indoor positioning technologies face challenges balancing low cost, low latency, and high accuracy, particularly in large underground parking lots (LUPLs). This paper proposes a sparsely deployed Bluetooth and magnetic (SBM) fusion positioning system for LUPL scenarios. Specifically, the spatial characteristics of the received signal strength indicator (RSSI) from sparsely deployed Bluetooth and the magnetic field strength are analyzed. Static and dynamic algorithms are designed for the SBM system by utilizing Bluetooth's area division and coarse positioning, combined with the high precision of magnetic field positioning. Experimental results from a real LUPL deployment demonstrate that, under a sparse beacon distribution (1 beacon per 294 m2), the proposed positioning algorithms achieve static accuracy of 1.32 m, dynamic accuracy of 0.75 m, and low latency on consumer-grade devices. © 2025 IEEE.

关键词： Global positioning system

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A UCA-Based Orbital Angular Momentum Solution for Integrated Sensing and Communication systems

A UCA-Based Orbital Angular Momentum Solution for Integrated...

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2025 IEEE Wireless Communications and networking Conference, WCNC 2025

作者： Zheng, Yihong Wang, Shumin Chu, Xinghe Zheng, Wei Hu, Zhiqun Lu, Zhaoming Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798350368369

In the sixth generation (6G) Internet of Things (IoT), integrated sensing and communication (ISAC) emerges as a key technology, which is expected to significantly enhance the perception capabilities and spectrum efficiency of base stations (BSs). It holds potential for applications in unmanned aerial vehicle (UAV) monitoring, vehicle positioning, and crowd detection. However, developing an integrated waveform that efficiently conserves spectrum resources while maintaining lower complexity remains challenging. This paper designs an ISAC system that utilizes orbital angular momentum (OAM) waves generated by a uniform circular array (UCA), which enhances communication and sensing capabilities by allocating distinct modes. This paper proposes a multimode multiplexing communication scheme based on a single UCA and an OAM-circular reception method (OAM-CRM) for the two-dimensional direction-of-arrival (DOA) estimation of targets, encompassing both azimuth and elevation angles. Additionally, an OAM-different modes (OAMDM) algorithm is designed to optimize communication and sensing performance across various mode sets. Simulation results verify the effectiveness of the OAM ISAC system and demonstrate the superior performance of the proposed algorithms compared to conventional methods. © 2025 IEEE.

关键词： Target drones

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Latency-Aware Server Deployment in Internet of Vehicles Based on Multi-Agent Reinforcement Learning

Latency-Aware Server Deployment in Internet of Vehicles Base...

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IEEE Conference on Wireless Communications and networking

作者： Xinran Liu Yaqiong Liu Junsheng Mu Guochu Shout Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

The performance of the servers directly affects the efficiency of the whole intelligent Internet of Vehicles (lo V) system. A reasonable server deployment strategy can effectively reduce network latency and improve the efficiency of ***, it is necessary to study the problem of server deployment in Io *** this paper, we formulate a latency-aware server deployment problem based on Multi-Agent Reinforcement Learning (MARL) and utilize an Actor-Critic network based on Long Short-Term Memory (LSTM) encoding network to solve it. Besides, four deployment strategies (DQN, DRQN, Random and No Movement) are used as the baseline methods for performance comparison with our proposed method on two real-world datasets. The simulation results show our solution has excellent performance in reducing network latency under different scenarios.

关键词： Training Simulation Transportation Reinforcement learning Encoding Stability analysis Servers

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One-Dimensional Bilateration Localization Algorithm Based on Indoor Distributed Antenna systems

One-Dimensional Bilateration Localization Algorithm Based on...

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IEEE Conference on Wireless Communications and networking

作者： Ruoqian Hu Xinghe Chu Zhaoming Lu Luhan Wang Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Indoor spaces have already been accounted for a significant proportion of people's lives, and with the advent of the fifth-generation mobile communication technology (5G) era and the rise of the Internet of Things (IoT), the demand for indoor localization is further increasing. Current solutions for indoor positioning, such as Bluetooth, Wi-Fi, ultra-wideband (UWB), and pseudo-satellite technologies, have faced issues in terms of cost, accuracy, and scalability during the promotion and application process. In this regard, distributed antenna systems (DAS) have an absolute advantage in terms of indoor coverage for communication, which shows enormous potential for fusion with current indoor positioning technologies. This paper proposed a universal one-dimensional localization algorithm fusing UWB technology with the indoor DAS system, aimed at narrow indoor environments such as corridors and cable tunnels, which can achieve high-precision localization as evaluated in a real scenario of an indoor corridor in the beijing University of Posts and Telecommunications (BUPT). Additionally, our algorithm requires only two anchors, effectively reducing positioning costs while improving accuracy. The results indicate that this localization technique effectively meets the requirements defined for indoor scenarios in 3GPP 38.855, with an error of decimeter level.

关键词： Location awareness Costs Accuracy Scalability Ultra wideband antennas Telecommunications Internet of Things 3GPP Wireless fidelity Antenna arrays

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