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Distributed Deep Learning for Cooperative Computation Offloading in Low Earth Orbit Satellite Networks

China Communications 2022年第4期19卷 230-243页

作者： Qingqing Tang zesong fei Bin Li School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing 210044China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and TelecommunicationsMinistry of EducationNanjing 210003China

Low earth orbit(LEO) satellite network is an important development trend for future mobile communication systems, which can truly realize the“ubiquitous connection” of the whole world. In this paper, we present a cooperative computation offloading in the LEO satellite network with a three-tier computation architecture by leveraging the vertical cooperation among ground users, LEO satellites, and the cloud server, and the horizontal cooperation between LEO satellites. To improve the quality of service for ground users, we optimize the computation offloading decisions to minimize the total execution delay for ground users subject to the limited battery capacity of ground users and the computation capability of each LEO satellite. However, the formulated problem is a large-scale nonlinear integer programming problem as the number of ground users and LEO satellites increases, which is difficult to solve with general optimization algorithms. To address this challenging problem, we propose a distributed deep learning-based cooperative computation offloading(DDLCCO) algorithm, where multiple parallel deep neural networks(DNNs) are adopted to learn the computation offloading strategy dynamically. Simulation results show that the proposed algorithm can achieve near-optimal performance with low computational complexity compared with other computation offloading strategies.

关键词： LEO satellite networks computation offloading deep neural networks

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Irregular repetition slotted ALOHA with total transmit power limitation

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Science China(Information Sciences) 2021年第2期64卷 264-265页

作者： Dai JIA zesong fei Yasheng ZHANG Science and Technology on Communication Networks Laboratory The 54th Research Institute of China Electronics Technology Group Corporation School of Information and Electronics Beijing Institute of Technology

Dear editor,The slotted ALOHA(SA) [1] protocol has been widely used in the multiple access networks, wherein the frame is divided into equal-length slots and all the users start their transmissions at the beginning of a slot. It should be noted that users cannot know whether other users are transmitting their packets or not. Owing to the independent transmission of users, collisions may happen, which can degrade the throughput performance. Therefore, it is necessary to manage the possible collisions rather than discard them [2–4].

关键词： Density Evolution Degree Distribution Coding Theory and Application Multiple Access Interference Cancellation Irregular Repetition Slotted ALOHA Throughput

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Robust capacity maximization transceiver design for MIMO OFDM systems

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Science China(Information Sciences) 2016年第6期59卷 119-129页

作者： Shaozhen GUO Chengwen XING zesong fei Dan LI School of Information and Electronics Beijing Institute of Technology

In this paper, we investigated capacity maximization problem for Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing systems with imperfect channel state information(CSI). To the best of our knowledge, the considered problem is still an open problem. However, the transceiver designs for MIMO OFDM systems have been extensively studied. It seems nobody gives closed-form solutions for resource allocation for MIMO OFDM systems with statistical channel estimation errors up to date. In our work, based on practical channel estimation algorithm, the channel estimation errors are first derived and then the robust resource allocation problem has been formulated. The structure of the optimal robust precoder is first derived,based on which the optimization problem will be simplified significantly. Furthermore, based on the Lagrangian dual method, a robust power allocation algorithm is proposed. The proposed power allocation can be considered as a variant of water-filling solution named cluster water-filling solution. Finally, simulation results show that our proposed robust design outperforms the non-robust design in terms of channel capacity.

关键词： MIMO-OFDM capacity maximization water-filling channel uncertainty robust design

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A QoE-based jointly subcarrier and power allocation for multiuser multiservice networks

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Science China Earth Sciences 2016年第12期59卷 34-46页

作者： Niwei WANG Shiqi GONG zesong fei Jingming KUANG School of Information and Electronics Beijing Institute of Technology

Quality of experience(QoE) is widely applied to reflect user's satisfaction of the network service,which exactly conforms to the user-centric concept in 5G. In this paper, we propose a QoE-based subcarrier and power allocation algorithm for the downlink transmission of a multiuser multiservice system. For the subcarrier allocation algorithm, the rate proportional fairness factor is defined to ensure the fairness between users. Based on different QoE models of three services, i.e., file down(FD), video streaming and voice over internet protocol(VOIP), a multi-objective optimization method is exploited to allocate the power resource by minimizing the total power consumption and maximizing the mean opinion score(MOS) value of users simultaneously. Simulation results indicate that the proposed algorithm has less power consumption and higher QoE performance than the traditional proportional fairness(PF) algorithm. In addition, the proposed algorithm can achieve nearly the same fairness performance as the PF algorithm. Moreover, when the number of subcarriers becomes larger, the power assumption will be less but with little influence on both the QoE and fairness performances.

关键词： QoE QoS MOS multiservice multi-objective optimization

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HAS QoE prediction based on dynamic video features with data mining in LTE network

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Science China(Information Sciences) 2017年第4期60卷 196-209页

作者： fei WANG zesong fei Jing WANG Yifan LIU Zhikun WU School of Information Science and Engineering Beijing Institute of Technology

Evaluation of HTTP adaptive streaming(HAS) quality of experience(Qo E) over LTE network is a challenging topic because of multi-segment and multi-rate features of dynamic video sequences. Different from the traditional Qo E evaluation methods based on network parameters, this paper proposes the HAS Qo E prediction methods based on its dynamic video segment features with data mining. Considering the application requirement of the trade-off between accuracy and complexity, two sets of methodologies are designed to evaluate the HAS Qo E including regression and classification. In regression method, we propose the evolved PSNR(e PSNR) model using differential peak signal to noise ratio(d PSNR) statistics as the segment features to evaluate HAS Qo E. In classification method, we propose the improved weighted k-nearest neighbors(Wk NN)by using dynamic weighted mapping according to the position of video chunk to meet the dynamic segment and rate features of HAS. In order to train and test these methods, we build a real-time HAS video-on-demand(VOD) system in LTE network and do subjective test in different video scenes. With the mean opinion score(MOS), the regression and classification methods are trained to predict the HAS Qo E. The validated results show that the proposed e PSNR and Wk NN methods outperform other evaluation methods.

关键词： HTTP adaptive streaming(HAS) quality of experience(Qo E) regression classification data mining video-on-demand(VOD) long term evolution(LTE)

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Performance analysis for uplink massive MIMO systems with a large and random number of UEs

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Science China(Information Sciences) 2016年第2期59卷 163-171页

作者： Ang YANG Chengwen XING zesong fei Jingming KUANG School of Information and Electronics Beijing Institute of Technology

In this paper, we analyze the ergodic achievable rate of an uplink massive multi-user multipleinput multiple-output(MIMO) system with a large and Poisson distributed number of users. In the considered scenario, multiple user equipments(UEs) transmit their information to a base station equipped with a very large number of antennas. New asymptotic expressions for the ergodic achievable rate for large and deterministic number of users are derived for both maximum ratio combining(MRC) detector and zero-forcing(ZF) detector,as well as the ergodic achievable rate for large and random number of users. Simulation results assess the accuracy of these analytical expressions. It is shown that compared with the MRC detector, ZF detector can achieve much higher spectrum efficiency. Also, the results provide a meaningful fact that with different settings the randomness of the number of users will result in different extents of impact on the performance of massive MIMO.

关键词： massive MIMO large numbers of UEs maximum ratio combining detector zero-forcing detector ergodic achievable rates

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Cooperative beamforming design for physical-layer security of multi-hop MIMO communications

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Science China(Information Sciences) 2016年第6期59卷 153-166页

作者： Shiqi GONG Chengwen XING zesong fei Jingming KUANG School of Information and Electronics Beijing Institute of Technology

The security issue is critically important for wireless communications, especially for multi-hop communications. In this paper, we propose a cooperative secrecy beamforming scheme for a multi-hop MIMO communication network, in which there is a single-antenna source, multiple multi-antenna relays and a singleantenna destination. Moreover, two types of eavesdroppers exist in the network, one of which has known channel state information(CSI), while the other not. To achieve security communications, in our work null-space beamforming and artificial noise beamforming are jointly optimized to improve the secrecy rate of the multi-hop network. In nature, the joint optimization is nonconvex and challenging. Exploiting its structure, the considered optimization problem is decoupled into a series of subproblems that can be efficiently solved based on convex optimization theory. Finally, some numerical experiment results are provided to assess the performance of the proposed secrecy beamforming design.

关键词： MIMO physical layer security multi-hop network null-space beamforming artificial noise

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On optimization of cooperative MIMO for underlaid secrecy Industrial Internet of Things

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Frontiers of Information Technology & Electronic Engineering 2023年第2期24卷 259-274页

作者： Xinyao WANG Xuyan BAO Yuzhen HUANG Zhong ZHENG zesong fei School of Information and Electronics Beijing Institute of TechnologyBeijing100081China China Academy of Information and Communications Technology Beijing100191China Academy of Military Sciences of PLA Beijing100091China

In this paper,physical layer security techniques are investigated for cooperative multi-input multi-output(C-MIMO),which operates as an underlaid cognitive radio system that coexists with a primary user(PU).The underlaid secrecy paradigm is enabled by improving the secrecy rate towards the C-MIMO receiver and reducing the interference towards the *** a communication model is especially suitable for implementing Industrial Internet of Things(IIoT)systems in the unlicensed spectrum,which can trade off spectral efficiency and information *** this end,we propose an eigenspace-adaptive precoding(EAP)method and formulate the secrecy rate optimization problem,which is subject to both the single device power constraint and the interference power *** precoder design is enabled by decomposing the original optimization problem into eigenspace selection and power allocation ***,the eigenvectors are adaptively selected by the transmitter according to the channel conditions of the underlaid users and the *** addition,a simplified EAP method is proposed for large-dimensional C-MIMO transmission,exploiting the additional spatial degree of freedom for a low-complexity secrecy precoder *** results show that by transmitting signal and artificial noise in the properly selected eigenspace,C-MIMO can eliminate the secrecy outage and outperforms the fixed eigenspace precoding ***,the proposed simplified EAP method for the large-dimensional C-MIMO can significantly improve the secrecy rate.

关键词： Cognitive radio network Physical layer security Cooperative multi-input multi-output(C-MIMO) Eigenspace-adaptive precoding Difference convex programming

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Resource Allocation for Physical Layer Security in Heterogeneous Network with Hidden Eavesdropper

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China Communications 2016年第3期13卷 82-95页

作者： GONG Shiqi XING Chengwen fei zesong KUANG Jingming School of Information and Electronics Beijing Institute of Technology

The tremendous performance gain of heterogeneous networks(Het Nets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for Het Nets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker(KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.

关键词： resource allocation physical layer security heterogeneous networks RSS-based location estimation lagrangian dual decomposition

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Intelligent Task Offloading and Collaborative Computation in Multi-UAV-Enabled Mobile Edge Computing

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China Communications 2022年第4期19卷 244-256页

作者： Jingming Xia Peng Wang Bin Li zesong fei Nanjing University of Information Science and Technology Nanjing 210044China Beijing Institute of Technology Beijing 100081China

This article establishes a three-tier mobile edge computing(MEC) network, which takes into account the cooperation between unmanned aerial vehicles(UAVs). In this MEC network, we aim to minimize the processing delay of tasks by jointly optimizing the deployment of UAVs and offloading decisions,while meeting the computing capacity constraint of UAVs. However, the resulting optimization problem is nonconvex, which cannot be solved by general optimization tools in an effective and efficient way. To this end, we propose a two-layer optimization algorithm to tackle the non-convexity of the problem by capitalizing on alternating optimization. In the upper level algorithm, we rely on differential evolution(DE) learning algorithm to solve the deployment of the UAVs. In the lower level algorithm, we exploit distributed deep neural network(DDNN) to generate offloading decisions. Numerical results demonstrate that the two-layer optimization algorithm can effectively obtain the near-optimal deployment of UAVs and offloading strategy with low complexity.

关键词： mobile edge computing multi-UAV collaborative cloud and edge computing deep neural network differential evolution

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