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Intelligent reflecting surface-assisted federated learning in multi-platoon collaborative networks

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Digital Communications and Networks 2023年第3期9卷 628-637页

作者： Xiaoting Ma junhui zhao Jieyu Liao Ziyang Zhang School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China China Telecom Corporation Limited Research Institute Beijing102209China School of Information Engineering East China Jiaotong UniversityNanchang330013China

Inspired by mobile edge computing(MEC),edge learning has gained a momentum by directly performing model training at network edge without sending massive data to a centralized data ***,the quality of model training will be affected by the limited communication and computing resources of network *** this paper,how to improve the training performance of a federated learning system aided by intelligent reflecting surface(IRS)over vehicle platooning networks is studied,where multiple platoons train a shared federated learning ***-platoon cooperation can alleviate the pressure of data processing caused by the limited computing resources of single ***,IRS can enhance the inter-platoon communication in a cost-effective and energy-efficient ***,the federated learning optimization problem of maximizing the learning accuracy is formulated by jointing platoon scheduling,bandwidth allocation and phase shifts at the IRS to maximize the number of scheduled ***-ically,in the proposed learning architecture each platoon updates the learning model with its own data and uploads it to the global model through IRS-based wireless ***,a method based on sequential optimization algorithm(SOA)and a group-based optimization method are analyzed for single IRS aided and large-scale IRS aided commu-nication,***,a platoon scheduling scheme is designed based on the communication reliability and computing reliability of *** results demonstrate that large-scale IRS assisted communication can effectively improve the reliability of multi-user communication *** scheduling scheme based on learning reliability balances the communication performance and computing performance of platoons.

关键词： Vehicle platooning networks Federated learning Intelligent reflecting surface Platoon scheduling Resource allocation

High-performance compensation scheme for frequency-dependent IQ imbalances in OFDM transmitter and receiver

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Journal of Systems Engineering and Electronics 2013年第2期24卷 204-208页

作者： Yan Liang Feng Shu Yijin Zhang junhui zhao School of Electronic Engineering and Optoelectronic Technology Nanjing University of Science and Technology College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications National Mobile Communications Research Laboratory Southeast University School of Electronic and Information Engineering Beijing Jiaotong University

An efficient compensation scheme combining a timedomain Gaussian elimination（GE） channel estimator and a frequency-domain GE equalizer is proposed for orthogonal frequency division multiplexing（OFDM） systems with frequencydependent in-phase and quadrature-phase（IQ） imbalances at both transmitter and *** with the traditional least square and least mean square compensation schemes,the proposed compensation scheme achieves the same bit error rate as the ideal IQ branches by using only two training OFDM symbols instead of about 20 OFDM symbols.

关键词： in-phase and quadrature-phase(IQ) imbalance time domain frequency domain least square least mean square Gaussian elimination(GE).

Secure and Efficient Computing Resource Management in Blockchain-Based Vehicular Fog Computing

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China Communications 2021年第4期18卷 115-125页

作者： Ming Kong junhui zhao Xiaoke Sun Yiwen Nie School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Information Engineering East China Jiaotong UniversityNanchang 330013China

In vehicular fog computing(VFC),the resource transactions in the Internet of Vehicles(IoV)have become a novel resource management scheme that can improve system resource utilization and the quality of vehicle *** this paper,in order to improve the security and fairness of resource transactions,we design a blockchain-based resource management scheme for ***,we propose the concept of resource coin(RC)and develop a blockchain-based secure computing reource trading mechanism in terms of *** a node of the blockchain network,the roadside unit(RSU)participates in verifying the legitimacy of transactions and the creation of new ***,we propose a resource management scheme based on contract theory,encouraging parked vehicles to contribute computing resource so that RSU could complete proof of work(PoW)quickly,improve the success probability of block creation and get RC *** use the gradient descent method to solve the computing resource utilization that can maximize the RC revenue of RSUs and vehicles during the block ***,the performance of this model is validated in simulation result and analysis.

关键词： blockchain vehicular fog computing resource management contract theory

Mobile Edge Computing Servers Deployment with Improved Genetic Algorithm in Cellular Internet of Things

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China Communications 2023年第9期20卷 215-226页

作者： Huan Zhang junhui zhao Lihua Yang Ziyang Zhang School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Information Engineering East China Jiaotong UniversityNanchang 330013China Lenovo Research Lenovo Group LimitedBeijing 100094China

Mobile edge computing(MEC)provides services to devices and reduces latency in cellular internet of things(IoT)***,the challenging problem is how to deploy MEC servers economically and *** paper investigates the deployment problem of MEC servers of the real-world road network by employing an improved genetic algorithm(GA)*** first use the threshold-based K-means algorithm to form vehicle clusters according to their *** then select base stations(BSs)based on clustering center coordinates as the deployment locations set for potential MEC *** further select BSs using a combined simulated annealing(SA)algorithm and GA to minimize the deployment *** simulation results show that the improved GA deploys MEC servers *** addition,the proposed algorithm outperforms GA and SA algorithms in terms of convergence speed and solution quality.

关键词： deployment of MEC servers IoT im-proved GA cost

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

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China Communications 2024年第5期21卷 113-122页

作者： Qiu Wanqing Zhang Qingmiao zhao junhui Yang Lihua School of Information Engineering East China Jiaotong UniversityNanchang 330013China School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related *** basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location ***,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy *** this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting ***,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it ***,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are ***,extensive simulation results are *** is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

关键词： extreme learning machine fingerprinting localization indoor localization machine learning particle swarm optimization

Cross-layer in MIMO-OFDM System with Adaptive Modulation and Coding:Design and Analysis

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Chinese Journal of Electronics 2014年第2期23卷 371-376页

作者： zhao junhui GUAN Xin LI Xiuping ZENG Longji State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University National Mobile Communications Research Laboratory Southeast University Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences School of Electronic Engineering Beijing University of Posts and Telecommunications

The queuing performance of the cross-layer system with Space-time block code(STBC) over Multiinput-multi-output(MIMO) channel is analyzed. The Adaptive modulation and coding(AMC) in physical layer and finite length of buffer in data-link layer are combined with this model. A simple cross-layer design and the queue state process are proposed based on finite state Markov channel model, which is to solve the service process. The proposed cross-layer design is also incorporated with STBC to further improve the system performance. Simulation results illustrate the dependence of system performance on various parameters, and quantify the performance gain due to cross-layer optimization. The adjustment of target packet loss rate of adaptive modulation coding in physical layer can maximize average throughput of the system,meanwhile a significant improvement of the system performance is brought.

关键词： Adaptive modulation and coding Crosslayer design Multi-input-multi-output Space-time block coding

Signal Path Reckoning Localization Method in Multipath Environment

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China Communications 2017年第3期14卷 182-189页

作者： junhui zhao Lei Li Hao Zhang Yi Gong School of Electronic and Information Engineering Beijing Jiaotong University School of Information Engineering East China Jiaotong University Department of Electrical and Electronic Engineering South University of Science and Technology of China

In the wireless localization application, multipath propagation seriously affects the localization accuracy. This paper presents two algorithms to solve the multipath problem. Firstly, we improve the Line of Possible Mobile Device(LPMD) algorithm by optimizing the utilization of the direct paths for single-bound scattering scenario. Secondly, the signal path reckoning method with the assistance of geographic information system is proposed to solve the problem of localization with multi-bound scattering paths. With the building model's idealization, the proposed method refers to the idea of ray tracing and dead reckoning. According to the rule of wireless signal reflection, the signal propagation path is reckoned using the measurements of emission angle and propagation distance, and then the estimated location can be obtained. Simulation shows that the proposed method obtains better results than the existing geometric localization methods in multipath environment when the angle error is controlled.

关键词： wireless localization multipath propagation signal reflection path reckoning

Energy-Efficient Computation Offloading and Resource Allocation in Fog Computing for Internet of Everything

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China Communications 2019年第3期16卷 32-41页

作者： Qiuping Li junhui zhao Yi Gong Qingmiao Zhang School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Information Engineering East China Jiaotong UniversityNanchang 330013China Shenzhen Engineering Laboratory of Intelligent Information Processing for IoT Southern University of Science and TechnologyShenzhen 518055China

With the dawning of the Internet of Everything(IoE) era, more and more novel applications are being deployed. However, resource constrained devices cannot fulfill the resource-requirements of these applications. This paper investigates the computation offloading problem of the coexistence and synergy between fog computing and cloud computing in IoE by jointly optimizing the offloading decisions, the allocation of computation resource and transmit power. Specifically, we propose an energy-efficient computation offloading and resource allocation(ECORA) scheme to minimize the system cost. The simulation results verify the proposed scheme can effectively decrease the system cost by up to 50% compared with the existing schemes, especially for the scenario that the computation resource of fog computing is relatively small or the number of devices increases.

关键词： fog computing cloud computing resource allocation computation offloading IoE

Deployment of Edge Computing Nodes in IoT:Effective Implementation of Simulated Annealing Method Based on User Location

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China Communications 2024年第1期21卷 279-296页

作者： junhui zhao Ziyang Zhang Zhenghao Yi Xiaoting Ma Qingmiao Zhang School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Information Engineering East China Jiaotong UniversityNanchang 330013China

Edge computing paradigm for 5G architecture has been considered as one of the most effective ways to realize low latency and highly reliable communication,which brings computing tasks and network resources to the edge of *** deployment of edge computing nodes is a key factor affecting the service performance of edge computing *** this paper,we propose a method for deploying edge computing nodes based on user *** the combination of Simulation of Urban Mobility(SUMO)and Network Simulator-3(NS-3),a simulation platform is built to generate data of hotspot areas in Io T *** effectively using the data generated by the communication between users in Io T scenario,the location area of the user terminal can be *** this basis,the deployment problem is expressed as a mixed integer linear problem,which can be solved by Simulated Annealing(SA)*** analysis of the results shows that,compared with the traditional method,the proposed method has faster convergence speed and better performance.

关键词： deployment problem edge computing internet of things machine learning