发帖
雷达卡
摘要翻译：
未来的移动网络正朝着异构多层网络的方向发展，在多层网络中，根据用户的需求部署各种类型的基站(BS)。因此，在BSs资源充足的情况下，合理利用BSs资源是十分必要的。本文提出了一种更真实的模型，该模型充分考虑了层间依赖性和用户与基站之间的依赖性，其中宏基站按齐次泊松点过程(PPP)分布，小基站按马特恩簇过程(MCP)分布，其父点位于MBSs的位置，以便从过载的MBSs中卸载用户。我们还假设用户只是随机地位于以MBSS为中心的圆圈中。在此模型下，我们用随机几何的方法推导了关联概率和平均遍历率。得到了一个有趣的结果，即MBS的密度和团簇半径以联合形式共同影响缔合概率。我们还观察到，与以前的蜂窝网络相比，使用分簇SBSs会导致积极的卸载。
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英文标题：
《User Association for Offloading in Heterogeneous Network Based on Matern
Cluster Process》
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作者：
Yuxuan Xie, Xuefei Zhang, Qimei Cui, and Yanyan Lu
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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：
Future mobile networks are converging toward heterogeneous multi-tier networks, where various classes of base stations (BS) are deployed based on user demand. So it is quite necessary to utilize the BSs resources rationally when BSs are sufficient. In this paper, we develop a more realistic model that fully considering the inter-tier dependence and the dependence between users and BSs, where the macro base stations (MBSs) are distributed according to a homogeneous Poisson point process (PPP) and the small base stations (SBSs) follows a Matern cluster process (MCP) whose parent points are located in the positions of the MBSs in order to offload the users from the over-loaded MBSs. We also assume the users are just randomly located in the circles centered at the MBSs. Under this model, we derive the association probability and the average ergodic rate by stochastic geometry. An interesting result that the density of MBS and the radius of the clusters jointly affect the association probabilities in a joint form is obtained. We also observe that using the clustered SBSs results in aggressive offloading compared with previous cellular networks.
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PDF链接：
https://arxiv.org/pdf/1802.09695
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