matlab行列式的代码行列式点过程学习 (DPPL) 论文“机器学习遇到随机几何：无线网络的行列式子集选择”的 Matlab 脚本 作者：Chiranjib Saha 和 Harpreet S. Dhillon 通信电子邮件： 论文链接： 该存储库包含论文“机器学习满足随机几何：无线网络的确定子集选择”中提出的 DPPL 的 matlab 脚本。 运行“TrainDPP.m”以生成结果。 在“GenerateTrainingSet”文件夹下，使用 generateTrainingSet.m 生成新的训练集。 如果代码被重用，请引用以下论文。 @article{saha2019load, title={Machine Learning meets Stochastic Geometry: {D}eterminantal Subset Selection for Wireless Networks}, author={Saha, Chiranjib and Dhillon, Harpreet S}, note={available online: arxiv.org/abs/1905.0

基于PPP随机几何方法以及蒙特卡洛方法对蜂窝通信通信系统进行仿真

为了应对未来通信网络更高速率和可靠性的需求蜂窝网的发展面临巨大挑战 一种可行的解决方案就是在蜂窝网络中部署中继站 同时由于通信网络能耗的降低已成为一个亟待解决的问题高能效的通信网络成为未来的发展趋势 该文基于随机几何模型研究了中继蜂窝网络的能效问题分别推导了宏基站一用户链路宏蜂窝一中继站链路和中继站一用户链路的覆盖概率并对宏基站和中继站的功耗进行了建模在此基础上推导出了下行中继蜂窝网络的能效表达式 仿真结果表明 随着宏基站密度增加网络能效性能会逐渐提升并最终收敛

随机几何图是一种无向空间图（或网络），其节点随机放置在二维正方形 [0,1] 中。 如果两个节点之间的欧几里得距离等于或小于某个半径，则它们通过边连接。 使用GUIDE创建的说明性应用程序可用于学习如何构造随机几何图并提供有关其外观的一些见解。 特征： - 节点数可以更改（10、30、50、100、200） - 半径可以变化（0.1、0.2、0.3、0.5） - 可以绘制以每个节点为中心的圆周。 - 可以求解 Adjancey 矩阵、节点坐标和创建的随机几何图的半径- 颜色条表示节点连接。 此外，plotRGG.m 函数可以单独用于绘制您自己的随机几何图形。 这是我第一次接触 GUI，所以如果有任何错误，请告诉我。 添加一名作者

随机几何理论是一本经典的学习教材，目前还没有国内完整的翻译版本。

教材stochastic geometry for wireless networks MARTIN HAENGGI

很难找到的一本电子书，非常厚，可做科研，用在无线网络研究或其他的研究上。

Stochastic Geometry and Wireless Networks Iⅈ 第一卷以及第二卷

Stochastic Geometry and Its Applications, 3rd Edition Sung Nok Chiu, Dietrich Stoyan, Wilfrid S. Kendall, Joseph Mecke ISBN: 978-0-470-66481-0 582 pages July 2013 Description An extensive update to a classic text Stochastic geometry and spatial statistics play a fundamental role in many modern branches of physics, materials sciences, engineering, biology and environmental sciences. They offer successful models for the description of random two- and three-dimensional micro and macro structures and statistical methods for their analysis. The previous edition of this book has served as the key reference in its field for over 18 years and is regarded as the best treatment of the subject of stochastic geometry, both as a subject with vital applications to spatial statistics and as a very interesting field of mathematics in its own right. This edition: Presents a wealth of models for spatial patterns and related statistical methods. Provides a great survey of the modern theory of random tessellations, including many new models that became tractable only in the last few years. Includes new sections on random networks and random graphs to review the recent ever growing interest in these areas. Provides an excellent introduction to theory and modelling of point processes, which covers some very latest developments. Illustrate the forefront theory of random sets, with many applications. Adds new results to the discussion of fibre and surface processes. Offers an updated collection of useful stereological methods. Includes 700 new references. Is written in an accessible style enabling non-mathematicians to benefit from this book. Provides a companion website hosting information on recent developments in the field www.wiley.com/go/cskm Stochastic Geometry and its Applications is ideally suited for researchers in physics, materials science, biology and ecological sciences as well as mathematicians and statisticians. It should also serve as a valuable introduction to the su

通过该PPT，可以简单了解无线通信中随机几何理论的基本方法