Machine Learning and Wireless Communications
Machine Learning and Wireless Communications
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机器学习和无线通信
DOI：
10.1017/9781108966559
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发表时间：
2022
影响因子：
8.3
通讯作者：
Kin K. Leung
中科院分区：
文献类型：
--
作者：
Y. Eldar;Andrea J. Goldsmith;H. V. Poor;Ziv Aharoni;Dor Tsur;Ziv Goldfeld;H. Permuter;Emre Ozfatura;Deniz Gündüz;Shiqiang Wang;Tiffany Tuor;Kin K. Leung
机器学习如何帮助设计未来的通信网络--未来的网络如何满足新兴的机器学习应用的需求？在这本综合性的书中，探索我们这个时代最具变革性和影响力的两项技术之间的相互作用。首先，学习现代机器学习技术，如深度神经网络，如何改变我们设计和优化未来通信网络的方式。对概念和工具的易懂介绍伴随着大量真实世界的示例，向您展示如何使用这些技术来解决长期存在的问题。接下来，探索将无线网络设计为机器学习应用程序的平台-概述现代机器学习技术和通信协议将帮助您了解挑战，同时将介绍新的方法和设计方法来处理无线信道损伤，如噪声和干扰，以满足无线边缘新兴的机器学习应用程序的需求。
How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.