Channel Estimation with Fully Connected Deep Neural Network

被引：0
作者：
Radosveta Sokullu
Mete Yıldırım
机构：
[1] Ege University,
来源：
Wireless Personal Communications | 2022年 / 125卷
关键词：
Channel estimation; Deep learning; Machine learning; Rayleigh channel;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this study, we focus on realizing channel estimation using a fully connected deep neural network. The data aided estimation approach is employed. We assume the transmission channel is Rayleigh and it is constant over the duration of a symbol plus pilot transmission. We develop and tune the deep learning model for various size of pilot data that is known to the receiver and used for channel estimation. The deep learning models are trained on the Rayleigh channel. The performance of the model is discussed for various size of pilot by providing Bit Error Rate of the model. The Bit Error Rate performance of the model is compared to theoretical upper bound which shows that the model successfully estimates the channel.
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页码：2305 / 2317
页数：12
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