Deep Over-the-Air Computation
Deep Over-the-Air Computation
复制标题
DOI：
10.1109/globecom42002.2020.9321975
复制
发表时间：
2020-12
期刊：
影响因子：
--
通讯作者：
Hao Ye;Geoffrey Y. Li;B. Juang
中科院分区：
文献类型：
--
作者：
Hao Ye;Geoffrey Y. Li;B. Juang
空中计算作为一种高效的数据融合方法，利用多接入信道的叠加特性，将计算和通信融为一体。本文提出了一种支持无线计算的深度学习框架，其中预处理和后处理功能均由深度神经网络（DNN）表示。通过这种方式，空中计算可以通过数据学习来逼近任何函数。深度无线框架对于物联网 (IoT) 上的各种机器学习应用非常有用。分布回归和异常检测实验证明了该方法的有效性。
As an efficient data fusion method, over-the-air computation integrates computation and communication by exploiting the superposition property of multiple access channels. In this paper, a framework on deep learning enabled over-the-air computation is proposed, where both the pre-processing and post-processing functions are represented by deep neural networks (DNNs). In this way, the over-the-air computation can approximate any function via learning through the data. The deep over-the-air framework is useful to a variety of machine learning applications on the Internet-of-Things (IoT). The experiments on distribution regression and anomaly detection have shown the effectiveness of the proposed method.