摘要翻译：
5G新无线将支持三大业务类别：增强型移动宽带(eMBB)、超可靠低时延通信(URLLC)和大规模机器型通信。新兴的URLLC服务需要高达一毫秒的通信延迟，成功概率为99.999%。然而，在系统频谱效率(SE)和可实现的延迟之间有一个基本的权衡。这就要求新的调度协议以用户为中心交叉优化系统性能；而不是以网络为中心的基础。本文提出了一种联合多用户抢占调度策略来同时交叉优化系统SE和URLLC时延。在每个调度机会，可用的URLLC流量总是被给予更高的优先级。当在传输时间间隔(TTI)内出现零星的URLLC流量时，提出的调度器寻求在多用户传输中拟合URLLC-eMBB流量。如果可用的空间自由度被限制在TTI内，URLLC业务立即覆盖部分正在进行的eMBB传输以满足URLLC延迟要求，代价是最小的eMBB吞吐量损失。大量的动态系统级仿真表明，所提出的调度器在eMBB、SE、URLLC延迟方面提供了显着的性能增益。
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英文标题：
《Multi-User Preemptive Scheduling for Critical Low Latency Communications
  in 5G Networks》
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作者：
Ali A. Esswie, Klaus I. Pedersen
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science        计算机科学
二级分类：Networking and Internet Architecture        网络和因特网体系结构
分类描述：Covers all aspects of computer communication networks, including network architecture and design, network protocols, and internetwork standards (like TCP/IP). Also includes topics, such as web caching, that are directly relevant to Internet architecture and performance. Roughly includes all of ACM Subject Class C.2 except C.2.4, which is more likely to have Distributed, Parallel, and Cluster Computing as the primary subject area.
涵盖计算机通信网络的所有方面，包括网络体系结构和设计、网络协议和网络间标准（如TCP/IP）。还包括与Internet体系结构和性能直接相关的主题，如web缓存。大致包括除C.2.4以外的所有ACM主题类C.2，后者更有可能将分布式、并行和集群计算作为主要主题领域。
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英文摘要：
  5G new radio is envisioned to support three major service classes: enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine type communications. Emerging URLLC services require up to one millisecond of communication latency with 99.999% success probability. Though, there is a fundamental trade-off between system spectral efficiency (SE) and achievable latency. This calls for novel scheduling protocols which cross-optimize system performance on user-centric; instead of network-centric basis. In this paper, we develop a joint multi-user preemptive scheduling strategy to simultaneously cross-optimize system SE and URLLC latency. At each scheduling opportunity, available URLLC traffic is always given higher priority. When sporadic URLLC traffic appears during a transmission time interval (TTI), proposed scheduler seeks for fitting the URLLC-eMBB traffic in a multi-user transmission. If the available spatial degrees of freedom are limited within a TTI, the URLLC traffic instantly overwrites part of the ongoing eMBB transmissions to satisfy the URLLC latency requirements, at the expense of minimal eMBB throughput loss. Extensive dynamic system level simulations show that proposed scheduler provides significant performance gain in terms of eMBB SE and URLLC latency.
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PDF链接：
https://arxiv.org/pdf/1806.04588