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Hybrid MPIE Method with Anisotropic Impedance Boundary Conditions for Layered Media

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Hybrid MPIE Method with Anisotropic Impedance Boundary Condi...

International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Ying Zhao Wenjie Neng Zhen Zhang Dazhi Ding College of computer and information engineering (College of artificial intelligence) Nanjing Tech University Nanjing China State Key Laboratory of Millimeter Waves Nanjing China China Key System & Integrated Circuit Co. Ltd. Wuxi China Department of communication engineering Nanjing University of Science and Technology Nanjing China

A mixed potential integral equation (MPIE) method combined with anisotropic impedance boundary conditions is proposed for the analysis of scattering from layered media. In this method, anisotropic surface conductivity is modeled by the impedance boundary conditions. As a result, only these surfaces need to be discretized. Numerical example is demonstrated to show the accuracy of this method.

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Towards Dynamic Resource Allocation and Client Scheduling in Hierarchical Federated Learning: A Two-Phase Deep Reinforcement Learning Approach

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arXiv 2024年

作者： Chen, Xiaojing Li, Zhenyuan Ni, Wei Wang, Xin Zhang, Shunqing Sun, Yanzan Xu, Shugong Pei, Qingqi The Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University Shanghai200444 China SydneyNSW2122 Australia The Department of Communication Science and Engineering Fudan University Shanghai200433 China The State Key Laboratory of Integrated Services Networks School of Telecommunications Engineering Xidian University Xi’an710071 China

Federated learning (FL) is a viable technique to train a shared machine learning model without sharing data. Hierarchical FL (HFL) system has yet to be studied regrading its multiple levels of energy, computation, communication, and client scheduling, especially when it comes to clients relying on energy harvesting to power their operations. This paper presents a new two-phase deep deterministic policy gradient (DDPG) framework, referred to as "TP-DDPG", to balance online the learning delay and model accuracy of an FL process in an energy harvesting-powered HFL system. The key idea is that we divide optimization decisions into two groups, and employ DDPG to learn one group in the first phase, while interpreting the other group as part of the environment to provide rewards for training the DDPG in the second phase. Specifically, the DDPG learns the selection of participating clients, and their CPU configurations and the transmission powers. A new straggler-aware client association and bandwidth allocation (SCABA) algorithm efficiently optimizes the other decisions and evaluates the reward for the DDPG. Experiments demonstrate that with substantially reduced number of learnable parameters, the TP-DDPG can quickly converge to effective polices that can shorten the training time of HFL by 39.4% compared to its benchmarks, when the required test accuracy of HFL is 0.9. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy harvesting

High-performance III-V/Si3N4 O-band External Cavity Tunable Laser

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High-performance III-V/Si3N4 O-band External Cavity Tunable ...

CLEO: science and Innovations, S and I 2022

作者： Guo, Yuyao Li, Xinhang Jin, Minhui Liu, Chuxin Xu, Weihan Lu, Liangjun Xie, Jingya Chen, Jianping Zhou, Linjie State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China Terahertz Technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation Center Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology Shanghai200093 China

We present a III-V/Si3N4 O-band hybrid laser, which shows a high output power of 42 mW, wide tuning range of 62 nm with side-mode suppression ratio >50 dB, and narrow intrinsic linewidth of ~600 Hz. © Optica P...

ISBN: (纸本)9781557528209

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Joint Beamforming Optimization and Mode Selection for RDARS-Aided MIMO systems

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arXiv 2024年

作者： Wang, Jintao Ma, Chengzhi Gong, Shiqi Yang, Xi Ma, Shaodan State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China Shanghai Key Laboratory of Multidimensional Information Processing School of Communication and Electronic Engineering East China Normal University Shanghai200241 China

Reconfigurable intelligent surface (RIS) has emerged as a cost-effective solution for green communications in 6G. However, its further extensive use has been greatly limited due to its fully passive characteristics. Considering the appealing distribution gains of distributed antenna systems (DAS), a flexible reconfigurable architecture called reconfigurable distributed antenna and reflecting surface (RDARS) is proposed. RDARS encompasses DAS and RIS as two special cases and maintains the advantages of distributed antennas while reducing the hardware cost by replacing some active antennas with low-cost passive reflecting surfaces. In this paper, we present a RDARS-aided uplink multi-user communication system and investigate the system transmission reliability with the newly proposed architecture. Specifically, in addition to the distribution gain and the reflection gain provided by the connection and reflection modes, respectively, we also consider the dynamic mode switching of each element which introduces an additional degree of freedom (DoF) and thus results in a selection gain. As such, we aim to minimize the total sum mean-square-error (MSE) of all data streams by jointly optimizing the receive beamforming matrix, the reflection phase shifts and the channel-aware placement of elements in the connection mode. To tackle this nonconvex problem with intractable binary and cardinality constraints, we propose an inexact block coordinate descent (BCD) based penalty dual decomposition (PDD) algorithm with the guaranteed convergence. Since the PDD algorithm usually suffers from high computational complexity, a low-complexity greedy-search-based alternating optimization (AO) algorithm is developed to yield a semi-closed-form solution with acceptable performance. Numerical results demonstrate the superiority of the proposed architecture compared to the conventional fully passive RIS or DAS. Furthermore, some insights about the practical implementation of RDARS are provided

关键词： Mean square error

LLM4WM: Adapting LLM for Wireless Multi-Tasking

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arXiv 2025年

作者： Liu, Xuanyu Gao, Shijian Liu, Boxun Cheng, Xiang Yang, Liuqing State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Guangzhou511400 China Guangzhou511400 China Department of Electronic and Computer Engineering The Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong

The wireless channel is fundamental to communication, encompassing numerous tasks collectively referred to as channel-associated tasks. These tasks can leverage joint learning based on channel characteristics to share representations and enhance system design. To capitalize on this advantage, LLM4WM is proposed—a large language model (LLM) multi-task fine-tuning framework specifically tailored for channel-associated tasks. This framework utilizes a Mixture of Experts with Low-Rank Adaptation (MoE-LoRA) approach for multi-task fine-tuning, enabling the transfer of the pre-trained LLM’s general knowledge to these tasks. Given the unique characteristics of wireless channel data, preprocessing modules, adapter modules, and multi-task output layers are designed to align the channel data with the LLM’s semantic feature space. Experiments on a channel-associated multi-task dataset demonstrate that LLM4WM outperforms existing methodologies in both full-sample and few-shot evaluations, owing to its robust multi-task joint modeling and transfer learning capabilities. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantics

Integrated adaptive coherent LiDAR for 4D bionic vision

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arXiv 2024年

作者： Chen, Ruixuan Wu, Yichen Zhang, Ke Liu, Chuxin Chen, Yikun Li, Wencan Shen, Bitao Chen, Zhaoxi Feng, Hanke Ge, Zhangfeng Zhou, Yan Tao, Zihan Xu, Weihan Wang, Yimeng Cai, Pengfei Pan, Dong Shu, Haowen Zhou, Linjie Wang, Cheng Wang, Xingjun State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Peking University Beijing100871 China Department of Electrical Engineering State Key Laboratory of Terahertz and Millimeter Waves City University of Hong Kong Hong Kong State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Peking University Yangtze Delta Institute of Optoelectronics Nantong226010 China Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China SiFotonics Technologies Co. Ltd. Beijing China

Light detection and ranging (LiDAR) is a ubiquitous tool to provide precise spatial awareness in various perception environments. A bionic LiDAR that can mimic human-like vision by adaptively gazing at selected regions of interest within a broad field of view is crucial to achieve high-resolution imaging in an energy-saving and cost-effective manner. However, current LiDARs based on stacking fixed-wavelength laser arrays and inertial scanning have not been able to achieve the desired dynamic focusing patterns and agile scalability simultaneously. Moreover, the ability to synchronously acquire multidimensional physical parameters, including distance, direction, Doppler, and color, through seamless fusion between multiple sensors, still remains elusive in LiDAR. Here, we overcome these limitations and demonstrate a bio-inspired frequency-modulated continuous wave (FMCW) LiDAR system with dynamic and scalable gazing capability. Our chip-scale LiDAR system is built using hybrid integrated photonic solutions, where a frequency-chirped external cavity laser provides broad spectral tunability, while on-chip electro-optic combs with elastic channel spacing allow customizable imaging granularity. Using the dynamic zoom-in capability and the coherent FMCW scheme, we achieve a state-of-the-art resolution of 0.012 degrees, providing up to 15 times the resolution of conventional 3D LiDAR sensors, with 115 equivalent scanning lines and 4D parallel imaging. We further demonstrate cooperative sensing between our adaptive coherent LiDAR and a camera to enable high-resolution color-enhanced machine vision. With its beyond-retinal resolution, flexible gazing ability, as well as low-cost chip manufacturability, our bionic LiDAR solution paves the way for high-resolution adaptive 4D-plus machine vision that could benefit a wide range of applications, including autonomous driving, intelligent robotics, and electric vertical take-off and landing (eVTOL) aircraft. © 2024, CC BY.

关键词： Intelligent robots

Multi-Functional Beamforming Design for Integrated Sensing, communication, and Computation

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IEEE Transactions on communications 2024年

作者： Zhao, Yapeng Wu, Qingqing Chen, Wen Zeng, Yong Liu, Ruiqi Mei, Weidong Hou, Fen Ma, Shaodan Shanghai Jiao Tong University Department of Electronic Engineering 200240 China University of Macau State Key Laboratory of Internet of Things for Smart City 999078 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China ZTE Corporation State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518057 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China University of Macau Department of Electrical and Computer Engineering 999078 China

Integrated sensing and communication (ISAC) systems may face a heavy computation burden since the sensory data needs to be further processed. This paper studies a novel system that integrates sensing, communication, and computation, aiming to provide services for different objectives efficiently. This system consists of a multi-antenna multi-functional base station (BS), an edge server, a target, and multiple single-antenna communication users. The BS needs to allocate the available resources to efficiently provide sensing, communication, and computation services. Due to the heavy service burden and limited power budget, the BS can partially offload the tasks to the nearby edge server instead of computing them locally. We consider the estimation of the target response matrix, a general problem in radar sensing, and utilize Cramér-Rao bound (CRB) as the corresponding performance metric. To tackle the non-convex optimization problem, we propose both semidefinite relaxation (SDR)-based alternating optimization and SDR-based successive convex approximation (SCA) algorithms to minimize the CRB of radar sensing while meeting the requirement of communication users and the need for task computing. Furthermore, we demonstrate that the optimal rank-one solutions of both the alternating and SCA algorithms can be directly obtained via the solver or further constructed even when dealing with multiple functionalities. Simulation results show that the proposed algorithms can provide higher target estimation performance than state-of-the-art benchmarks while satisfying the communication and computation constraints. © 1972-2012 IEEE.

关键词： Convex optimization

Extended NNs-Based Adaptive Event-Triggered Asymptotic Control for Nonlinear systems Against Actuator Faults

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Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

International Symposium on Autonomous systems (ISAS)

作者： Shanlin Liu Yingwei Zhang Xudong Zhao Hesheng Wang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of IntelligentControl and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent.

关键词： Actuators Backstepping Fault tolerant systems Process control Artificial neural networks Control systems Approximation error

Fea Study on the Tsv Copper Filling Influenced by the Additives and Electroplating Process

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SSRN

SSRN 2023年

作者： Zhao, Zifeng Liu, Ziyu Chen, Lin Sun, Qingqing Liu, Hongye Sun, Yabin School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai200433 China Jiashan Fudan Institute Zhejiang Province Jiaxing314100 China Department of Electrical Engineering East China Normal University Shanghai200241 China

Abstract Through-Silicon Via (TSV) is a key technology of three-dimensional (3D) integration. However, it is easy to have voids in the Cu filling process of TSV. Additives and optimized filling process are used to solve this problem. However, the comprehensive analysis of these affecting parameter needs many experiments and cost much time. Thus, the finite element analysis (FEA) for the mass transferring of electroplating is carried out by the COMSOL software in the work. The filling processes with different inhibitor concentrations are first studied and the most suitable density of 64mol/m2 is obtained. However, high inhibitor concentration will lead to much lower plating speed. Thus, the effect of filling process such as current density and plating bath flow velocity on the voids are investigated under the optimized concentrations above. The best filling quality is obtained at the current density of 1.4 ASD and the bath stirring velocity of 0.4 m/s. The underlying growth mechanism of these influencing factors are also analyzed and revealed. © 2023, The Authors. All rights reserved.

关键词： Copper