专题:6G的智能通信计算融合技术

内容导读目前,针对潜在6G关键技术的场景与需求研究成为学术界的热点。面向未来更多类型终端的智能互联与新兴服务的需求,人工智能应用于无线通信物理层的信道估计、编译码及接收机设计,解决基于大数据的网络自主优化,基于泛在无线感知和边缘侧的强大算力构成的多接入边缘计算,已成为6G无线技术发展的重要趋势。在未来智能车联网、物联网、有人/无人交互、全息通信等场景下,面向未来的智能通信计算融合需求,存在许多拟待解决的关键科学问题。     

基于MSTP以太网专线远程视音频传输的分析和实现

基于MSTP以太网专线进行远程视音频传输,是一种结构简单、线路便宜、容易搭建的传输系统.由于MSTP以太网专线的独特设计,点到点的透传方式,容易实现对用户MAC帧点到点的透传,在线路上能独享带宽,业务延迟小,且和其它业务完全隔离,安全性高,这种业务适合广播级视音频信号远程传输的应用.     

Controlled Secure Direct Communication Protocol via the Three-Qubit Partially Entangled Set of States

In this paper, we first re-examine the previous protocol of controlled quantum secure direct communication of Zhang et al.’s scheme, which was found insecure under two kinds of attacks, fake entangled particles attack and disentanglement attack. Then, by changing the party of the preparation of cluster states and using unitary operations, we present an improved protocol which can avoid these two kinds of attacks. Moreover, the protocol is proposed using the three-qubit partially entangled set of states. It is more efficient by only using three particles rather than four or even more to transmit one bit secret information. Given our using state is much easier to prepare for multiqubit states and our protocol needs less measurement resource, it makes this protocol more convenient from an applied point of view.     

关于加强员工考勤管理工作的几点思考

本文介绍了江汉油田员工考勤管理工作的基本情况,梳理和分析了当前员工考勤管理中存在的问题及原因,提出了要进一步细化和完善管理制度,强化过程监督和责任落实,逐步推进考勤公示制度化等措施。     

基于光纤技术的采空区发火监测系统的应用

基于光纤技术的采空区发火监测系统由传感器、数据传输、数据分析与控制三大部分构成,研发新一代适合煤矿安全领域应用的先进传感器、并以此为基础构建新型煤矿安全灾害监测预警系统,对于实现煤矿安全发展具有十分重要的意义。     

基于Q-learning的不确定环境BDI Agent最优策略规划研究

BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。     

乌江索风营水电站地下厂房岩锚梁镜面混凝土施工技术

镜面混凝土是水电工程建设中新兴的一门施工技术,在乌江索风营水电站地下厂房岩锚梁混凝土施工中采用了镜面混凝土,这在技术上是一次大胆的尝试和创新,既满足了功能上的要求,同时也达到了美观和装饰地下厂房的效果,为今后水电工程施工中广泛采用镜面混凝土技术提供了样本和宝贵经验。     

Uplink Scheduling in CDMA Packet-Data Systems

Uplink scheduling in wireless systems is gaining importance due to arising uplink intensive data services (ftp, image uploads etc.), which could be hampered by the currently in-built asymmetry in favor of the downlink. In this work, we propose and study algorithms for efficient uplink packet-data scheduling in a CDMA cell. The algorithms attempt to maximize system throughput under transmit power limitations on the mobiles assuming instantaneous knowledge of user queues and channels. However no channel statistics or traffic characterization is necessary. Apart from increasing throughput, the algorithms also improve fairness of service among users, hence reducing chances of buffer overflows for poorly located users. The major observation arising from our analysis is that it is advantageous on the uplink to schedule “strong” users one-at-a-time, and “weak” users in larger groups. This contrasts with the downlink where one-at-a-time transmission for all users has shown to be the preferred mode in much previous work. Based on the optimal schedules, we propose less complex and more practical approximate methods, both of which offer significant performance improvement compared to one-at-a-time transmission, and the widely acclaimed Proportional Fair (PF) algorithm, in simulations. When queue content cannot be fed back, we propose a simple modification of PF, Uplink PF (UPF), that offers similar improvement. Hereafter, we refer to users with low recieved power at the base even when transmitting at peak transmit power as “weak” users, and the strongly recieved users at the base as “strong” users. Krishnan Kumaran is currently a member of the Complex Systems Modeling section in the Corporate Strategic Research of ExxonMobil Corp., Clinton, NJ. Formerly, he was a Member of Technical Staff in the Mathematics of Networks and Systems Research Department at Bell Labs in Murray Hill, NJ, where his research interests were in modeling, analysis and simulation of design, resource management and scheduling issues in telecommunication networks. Lijun Qian is an assistant professor in the Department of Electrical Engineering at Prairie View A&M University. He received his B.S. from Tsinghua University in Beijing, M.S. from Technion-Israel Institute of Technology, and Ph.D. from WINLAB, Rutgers University, all in electrical engineering. Before joining PVAMU, he was a researcher at Networks and Systems Research Department of Bell Labs in Murray Hill, NJ. His major research interests are in wireless communications and networking technologies, especially in radio resource management, protocol design, TCP/RLP optimization and MPLS traffic engineering.