摘要翻译：
随着业务需求的增长，对网络资源有效利用的需求不断增加，然而，目前移动通信系统的规划和部署都是为了提高无线覆盖范围和容量。不幸的是，这种方法已经不可持续了，因为5G通信系统将不得不应对大量的流量，在延迟和其他服务质量（Qualityof-Service,QoS）需求方面是异构的。此外，多址边缘计算(MEC)的出现提出了通过联合开发可用的无线资源和处理资源来更有效地规划和维度网络部署的需求。从这个角度来看，先进的用户小区关联可以对5G系统起到关键作用。本文以异构网络（HetNet）为研究对象，以上行链路(UL)中的任务卸载为例，对现有的无线小区关联规则和MEC感知小区关联规则进行了比较。数值计算结果表明，与标准的无线电独占规则相比，所提出的小区关联规则提供了近60%的延迟减少。
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英文标题：
《MEC-aware Cell Association for 5G Heterogeneous Networks》
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作者：
Mustafa Emara, Miltiades C. Filippou, Dario Sabella
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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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英文摘要：
  The need for efficient use of network resources is continuously increasing with the grow of traffic demand, however, current mobile systems have been planned and deployed so far with the mere aim of enhancing radio coverage and capacity. Unfortunately, this approach is not sustainable anymore, as 5G communication systems will have to cope with huge amounts of traffic, heterogeneous in terms of latency among other Qualityof- Service (QoS) requirements. Moreover, the advent of Multiaccess Edge Computing (MEC) brings up the need to more efficiently plan and dimension network deployment by means of jointly exploiting the available radio and processing resources. From this standpoint, advanced cell association of users can play a key role for 5G systems. Focusing on a Heterogeneous Network (HetNet), this paper proposes a comparison between state-of-the-art (i.e., radio-only) and MEC-aware cell association rules, taking the scenario of task offloading in the Uplink (UL) as an example. Numerical evaluations show that the proposed cell association rule provides nearly 60% latency reduction, as compared to its standard, radio-exclusive counterpart.
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PDF链接：
https://arxiv.org/pdf/1711.07217