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Coverage performance of the multilayer UAV-terrestrial HetNet with CoMP transmission scheme

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Frontiers of Information Technology & Electronic Engineering 2022年第1期23卷 61-72页

作者： Weihao WANG Yifan JIANG zesong fei Jing GUO School of Information and Electronics Beijing Institute of TechnologyBeijing100081China

To support the ubiquitous connectivity requirement of sixth generation communication,unmanned aerial vehicles(UAVs)play a key role as a major part of the future communication networks.One major issue in UAV communications is the interference resulting from spectrum sharing and line-of-sight links.Recently,the application of the coordinated multipoint(CoMP)technology has been proposed to reduce the interference in the UAV-terrestrial heterogeneous network(HetNet).In this paper,we consider a three-dimensional(3D)multilayer UAV-terrestrial HetNet,where the aerial base stations(ABSs)are deployed at multiple different altitudes.Using stochastic geometry,we develop a tractable mathematical framework to characterize the aggregate interference and evaluate the coverage probability of this HetNet.Our numerical results show that the implementation of the CoMP scheme can effectively reduce the interference in the network,especially when the density of base stations is relatively large.Furthermore,the system parameters of the ABSs deployed at higher altitudes dominantly influence the coverage performance of the considered 3D HetNet.

关键词： Unmanned aerial vehicle Poisson point process Coordinated multipoint(CoMP) Statistics of interference Coverage performance

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

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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

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 PU.Such 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 secrecy.To 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 constraint.This precoder design is enabled by decomposing the original optimization problem into eigenspace selection and power allocation sub-problems.Herein,the eigenvectors are adaptively selected by the transmitter according to the channel conditions of the underlaid users and the PUs.In 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 design.Numerical 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 methods.Moreover,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

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

Precoder design in downlink Co MP-JT MIMO network via WMMSE and asynchronous ADMM

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Science China(Information Sciences) 2018年第8期61卷 209-221页

作者： Zhikun WU zesong fei School of Information Science and Engineering Beijing Institute of Technology

Precoder design of coordinated multi-point joint transmission(Co MP-JT) multiple-input and multiple-output(MIMO) network aimied at throughput maximization is a challenging problem. In this paper, we propose an asynchronous distributed iterative method to solve this problem. We transform the original throughput maximizing problem to the weighted minimum mean square error(WMMSE) problem,then decompose the problem into a series of subproblems. Based on alternation direction method of multipliers(ADMM), the proposed algorithm can solve the optimal precoder in a distributed manner. With asynchronous information exchange mechanism considered, the convergence rate of our algorithm can be accelerated further. Numerical results demonstrate the increase of throughput and the optimality of the precoding scheme provided by our algorithm.

关键词： multiple-input and multiple-output coordinated multi-point joint transmission weighted minimum mean square error block coordinate descent alternation direction method of multipliers asynchronous method

Probabilistic-constrained robust secure transmission for energy harvesting over MISO channels

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Science China(Information Sciences) 2018年第2期61卷 65-76页

作者： Bin LI zesong fei School of Information and Electronics Beijing Institute of Technology

In this paper, we consider a system supporting simultaneous wireless information and power transfer(SWIPT), where the transmitter delivers private message to a destination receiver(DR) and powers to multiple energy receivers(ERs) with multiple single-antenna external eavesdroppers(Eves). We study secure robust beamformer and power splitting(PS) design under imperfect channel state information(CSI).The artificial noise(AN) scheme is further utilized at the transmitter to provide strong wireless security. We aim at maximizing the energy harvested by ERs subject to the transmission power constraint, a range of outage constraints concerning the signal-to-interference-plus-noise ratio(SINR) recorded at the DR and the Eves, as well as concerning the energy harvested at the DR. The energy harvesting maximization(EHM)problem is challenging to directly solve, we resort to Bernstein-type inequality restriction technique to reformulate the original problem as a tractable approximated version. Numerical results show that our robust beamforming scheme outperforms the beamforming scheme relying on the worst-case design philosophy.

关键词： secure communication wireless power transfer power splitting Bernstein-type inequality robust beamforming

HAS Dynamic Buffer-Driven Resource Management to Enhance QoE in Mobile Network

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China Communications 2017年第7期14卷 11-24页

作者： fei Wang zesong fei Jing Wang School of Information and Electronics Beijing Institute of Technology

Hypertext transfer protocol(HTTP) adaptive streaming(HAS) plays a key role in mobile video transmission. Considering the multi-segment and multi-rate features of HAS, this paper proposes a buffer-driven resource management(BDRM) method to enhance HAS quality of experience(QoE) in mobile network. Different from the traditional methods only focusing on base station side without considering the buffer, the proposed method takes both station and client sides into account and end user's buffer plays as the drive of whole schedule process. The proposed HAS QoE influencing factors are composed of initial delay, rebuffering and quality level. The BDRM method decomposes the HAS QoE maximization problem into client and base station sides separately to solve it in multicell and multi-user video playing scene in mobile network. In client side, the decision is made based on buffer probe and rate request algorithm by each user separately. It guarantees the less rebuffering events and decides which HAS segment rate to fetch. While, in the base station side, the schedule of wireless resource is made to maximize the quality level of all access clients and decides the final rate pulled from HAS server. The drive of buffer and twice rate request schemes make BDRMtake full advantage of HAS's multi-segment and multi-rate features. As to the simulation results, compared with proportional fair(PF), Max C/I and traditional HAS schedule(THS) methods, the proposed BDRM method decreases rebuffering percent to 1.96% from 11.1% with PF and from 7.01% with THS and increases the mean MOS of all users to 3.94 from 3.42 with PF method and from 2.15 with Max C/I method. It also guarantees a high fairness with 0.98 from the view of objective and subjective assessment metrics.

关键词：动态缓冲区移动网络资源管理驱动超文本传输协议最大化问题终端用户平均方法

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智能增强的免授权多址接入技术

中兴通讯技术 2024年第1期30卷 33-40页

作者：于含笑费泽松北京理工大学通信技术研究所中国北京100081

免授权多址接入技术是未来海量物联(IoT)场景的关键使能技术。在免授权接入系统中,由于用户和基站间缺少授权信息,易产生用户难识别以及用户间强干扰等问题,一方面可将免授权多址技术与非正交多址接入技术结合来缓解随机接入造成的用户... 详细信息

免授权多址接入技术是未来海量物联(IoT)场景的关键使能技术。在免授权接入系统中,由于用户和基站间缺少授权信息,易产生用户难识别以及用户间强干扰等问题,一方面可将免授权多址技术与非正交多址接入技术结合来缓解随机接入造成的用户干扰问题,另一方面也可以进一步利用人工智能技术强大的数据特征提取能力,对收发机算法进行优化,以有效降低用户碰撞概率,实现海量物联场景下的大规模通信。分析了当前未来移动通信网络中多址接入技术的需求、发展历程及研究现状。指出未来需要针对全场景进行接入技术拓展和智能技术弹性演进研究,以助力智能内生多址技术发展。

关键词：免授权接入海量物联非正交多址接入人工智能

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)