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Consistent and Accurate TDOA Localization in Dynamic NLOS Environments via Prior Information Independent Estimation

China communications 2024年第9期21卷 198-210页

作者： Luo Mei Long Yu Xiong Youzhi Qin Shuang Key Laboratory of Wireless Sensor Network in University of Sichuan Province College of Physics and Electronic EngineeringSichuan Normal UniversityChengdu 610101China

In the time-difference-of-arrival(TDOA)localization,robust least squares(LS)problems solved by mathematical programming were proven to be superior in mitigating the effects of non-line-of-sight(NLOS)***,the existing algorithms still suffer from two disadvantages:1)The algorithms strongly depend on prior information;2)The approaches do not satisfy the mean square error(MSE)optimal criterion of the measurement *** tackle the troubles,we first formulate an MSE minimization model for measurement noise by taking the source and the NLOS biases as *** obtain stable solutions,we introduce a penalty function to avoid abnormal *** further tackle the nonconvex locating problem with semidefinite relaxation ***,we incorporate mixed constraints and variable information to improve the estimation *** and experiments show that the proposed method achieves consistent performance and good accuracy in dynamic NLOS environments.

关键词： mathematical programming NLOS mitigation robust least squares TDOA

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Optimization-based mode selection scheme for OAM millimeter wave system in the off-axis misalignment case

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Digital communications and networks 2024年第1期10卷 101-108页

作者： Haie Dou Lei Wang Bin Kang Baoyu Zheng Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing210003China School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing210003China

Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system ***,to fulfill this advantage,the antennas at the transmitter and receiver must be parallel and coaxial;otherwise,the accuracy of mode detection at the receiver can be seriously *** this paper,we design an OAM millimeter-wave communication system for overcoming the above ***,the first contribution is that the power distribution between different OAM modes and the capacity of the system with different mode sets are analytically derived for performance *** second contribution lies in that a novel mode selection scheme is proposed to reduce the total interference between different *** results show that system performance is less affected by the offset when the mode set with smaller modes or larger intervals is selected.

关键词： Orbital angular momentum Millimeter wave Off-axis misalignment Mode selection Capacity

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Joint Optimization of Resource Allocation and Trajectory Based on User Trajectory for UAV-Assisted Backscatter communication System

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China communications 2024年第2期21卷 197-209页

作者： Peizhong Xie Junjie Jiang Ting Li Yin Lu School of Communication and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of EducationNanjing 210003China

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization *** iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.

关键词： energy efficiency joint optimization UAV-assisted backscatter communication user trajectory

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Federated Knowledge Distillation Enabled Image Semantic communication

Federated Knowledge Distillation Enabled Image Semantic Comm...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Xu, Xinmian Zheng, Kaipeng Dou, Haie Chen, Mingkai Wang, Lei Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing210003 China

ISBN: (纸本)9798350351255

The transition from 5G to beyond 5G (B5G) heralds a shift towards more pervasive and intelligent communication trends. This evolution necessitates a departure from traditional information theory towards semantic communication (SemCom), propelled by artificial intelligence (AI), aimed at enhancing capacity and optimizing resources. Concurrently, image SemCom (ISC) emerges to empower image applications. However, ISC demands suitable devices and ample computing resources to support complex neural network models and their training, presenting a significant challenge. In response, we propose a federated semantic feature distillation (FedSFD) architecture to enhance the overall performance of ISC. Combining federated learning (FL) and feature distillation (FD), FedSFD facilitates the transfer of group feature knowledge. Specifically, the powerful server model refines itself by approximating the distance between its middle layer features and those of the devices via FD. Subsequently, lightweight device ISC models leverage FD to incorporate the server model's knowledge during training. This iterative process is bolstered by the information bottleneck (IB)-based loss function, enhancing image compression and reconstruction capabilities. Notably, this architecture operates without necessitating a unified model, thereby offering improved privacy protection. Simulation experiments demonstrate that compared to the baseline, our approach can achieve superior integration capability for ISC at the noisy edge. © 2024 IEEE.

关键词： Federated learning

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Game-Theoretic Deep Reinforcement Learning for Task Offloading in Heterogeneous MEC Systems 16

Game-Theoretic Deep Reinforcement Learning for Task Offloadi...

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16th International Conference on wireless communications and Signal Processing, WCSP 2024

作者： Yu, Han Dou, Haie Xu, Xinmian Cui, Jingwu Wang, Lei Liu, Chen Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing210003 China

ISBN: (纸本)9798350390643

The emergence of new applications has increased the demand of mobile users for edge computing. Therefore, the optimization of base station load balancing and task offloading is particularly important. In this paper, a two-tier heterogeneous mobile edge computing (MEC) system based on Stackelberg Game (SG) is studied. The introduction of SG can improve user association flexibility while reducing base station load. The introduction of network slicing can classify users according to different types, which increases the universality of the proposed framework. To solve the above problem, we map an optimization problem of efficiency, computation delay and computation energy consumption. Due to the non-convexity of the optimization problem, the Multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm based on SG is proposed in this paper. The gradient descent strategy can converge faster and obtain the optimal solution of user association policy and unload policy. Through simulation, it is verified that the proposed scheme can obtain lower computation delay and computation energy consumption on the basis of solving the problem of base station overload. © 2024 IEEE.

关键词： Deep reinforcement learning

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Reinforcement Learning from Human-like Feedback Enhances Semantic communication with Multimodal LLMs 16

Reinforcement Learning from Human-like Feedback Enhances Sem...

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16th International Conference on wireless communications and Signal Processing, WCSP 2024

作者： Zhang, Xinyu He, Xitao Chen, Mingkai Wang, Lei Ministry of Education Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China

ISBN: (纸本)9798350390643

Semantic communication is an emerging intelligent paradigm that provides some special solutions for the various future applications. With the rise of large language model (LLM), it may enhance well on semantic communication. However, how to balance on the accuracy and the efficiency of compression remains an urgent issue to semantic communication with LLMs. In this paper, we design a multimodal large language models (MLLMs)-enabled semantic communication system specifically designed for image transmission, where the reinforcement learning from human-like feedback (RLHLF) framework is proposed to apply reasoning and self-reflection capabilities of MLLMs to enhance the quality of semantic extraction and image generation. For one thing, we first optimize the image semantic information at the transmitter by RLHLF framework. For another thing, the generated images are optimized at the receiver by RLHLF framework. Simulation results show that our proposed system provides bandwidth savings and enables graceful performance improvement as the channel quality improves, which proves the potential of MLLMs for future semantic communication. © 2024 IEEE.

关键词： Channel coding

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Dual Radial-Resonant Wide Beamwidth Circular Sector Microstrip Patch Antennas

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Chinese Journal of Electronics 2023年第4期32卷 710-719页

作者： MAO Xiaohui LU Wenjun JI Feiyan XING Xiuqiong ZHU Lei Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau

In this article, a design approach to a radial-resonant wide beamwidth circular sector patch antenna is advanced. As properly evolved from a U-shaped d ipole, a prototype magnetic dipole can be fit in the radial direction of a circular sector patch radiator, with its length set as the positive odd-integer multiples of onequarter wavelength. In this way, multiple TM0m（m = 1,2,...） modes resonant circular sector patch antenna with short-circuited circumference and widened E-plane beamwidth can be realized by proper excitation and perturbations. Prototype antennas are then designed and fabricated to validate the design approach. Experimental results reveal that the E-plane beamwidth of a dual-resonant antenna fabricated on air/Teflon substrate can be effectively broadened to 128°/120°, with an impedance bandwidth of 17.4%/7.1%, respectively. In both cases, the antenna heights are strictly limited to no more than 0.03-guided wavelength. It is evidently validated that the proposed approach can effectively enhance the operational bandwidth and beamwidth of a microstrip patch antenna while maintaining its inherent low profile merit.

关键词： Geometry Patch antennas Perturbation methods Prototypes Magnetic resonance Microstrip antennas Bandwidth

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Low-Complexity Estimation Algorithm and Decoupling Scheme for FRaC System

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Sun, Mengjiang Chen, Peng Cao, Zhenxin Shen, Fei State Key Laboratory of Millimeter Waves Southeast University Nanjing China Key Laboratory of Wireless Sensor Network and Communications Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China

With the leaping advances in autonomous vehicles and transportation infrastructure, dual function radarcommunication (DFRC) systems have become attractive due to the size, cost and resource efficiency. A frequency modulated continuous waveform (FMCW)-based radar-communication system (FRaC) utilizing both sparse multiple-input and multipleoutput (MIMO) arrays and index modulation (IM) has been proposed to form a DFRC system specifically designed for vehicular applications. In this paper, the three-dimensional (3D) parameter estimation problem in the FRaC is considered. Since the 3D-parameters including range, direction of arrival (DOA) and velocity are coupled in the estimating matrix of the FRaC system, the existing estimation algorithms cannot estimate the 3D-parameters accurately. Hence, a novel decomposed decoupled atomic norm minimization (DANM) method is proposed by splitting the 3D-parameter estimating matrix into multiple 2D matrices with sparsity constraints. Then, the 3D-parameters are estimated and efficiently and separately with the optimized decoupled estimating matrix. Moreover, the Cramer-Rao lower ´ bound (CRLB) of the 3D-parameter estimation are derived, and the computational complexity of the proposed algorithm is analyzed. Simulation results show that the proposed decomposed DANM method exploits the advantage of the virtual aperture in the existence of coupling caused by IM and sparse MIMO array and outperforms the co-estimation algorithm with lower computation complexity. IEEE

关键词： Computational complexity

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Generation of orbital angular momentum hologram using a modified U-net

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Chinese Physics B 2024年第3期33卷 401-407页

作者：郑志刚韩菲菲王乐赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China National Laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

Orbital angular momentum(OAM)holography has become a promising technique in information encryption,data storage and opto-electronic computing,owing to the infinite topological charge of one single OAM mode and the orthogonality of different OAM *** this paper,we propose a novel OAM hologram generation method based on a densely connected U-net(DCU),where the densely connected convolution blocks(DCB)replace the convolution blocks of the ***,the reconstruction process of the OAM hologram is integrated into DCU as its output layer,so as to eliminate the requirement to prepare training data for the OAM hologram,which is required by conventional neural networks through an iterative *** experimental and simulation results show that the OAM hologram can rapidly be generated with the well-trained DCU,and the reconstructed image's quality from the generated OAM hologram is significantly improved in comparison with those from the Gerchberg-Saxton generation method,the Gerchberg-Saxton based generation method and the U-net *** addition,a 10-bit OAM multiplexing hologram scheme is numerically demonstrated to have a high capacity with OAM hologram.

关键词： orbital angular momentum(OAM) holography OAM holography deep learning

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Diffraction deep neural network based orbital angular momentum mode recognition scheme in oceanic turbulence

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Chinese Physics B 2023年第4期32卷 364-369页

作者：詹海潮陈兵彭怡翔王乐王文鼐赵生妹 Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications(NUPT)Nanjing 210003China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China

Orbital angular momentum(OAM)has the characteristics of mutual orthogonality between modes,and has been applied to underwater wireless optical communication(UWOC)systems to increase the channel *** this work,we propose a diffractive deep neural network(DDNN)based OAM mode recognition scheme,where the DDNN is trained to capture the features of the intensity distribution of the OAM modes and output the corresponding azimuthal indices and radial *** results show that the proposed scheme can recognize the azimuthal indices and radial indices of the OAM modes accurately and *** addition,the proposed scheme can resist weak oceanic turbulence(OT),and exhibit excellent ability to recognize OAM modes in a strong OT *** DDNN-based OAM mode recognition scheme has potential applications in UWOC systems.

关键词： orbital angular momentum diffractive deep neural network mode recognition oceanic turbulence

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