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About Deep Learning Channel Estimation
1. This document proposes using deep learning techniques for channel estimation in massive MIMO systems that use mixed-resolution ADCs (analog-to-digital converters), where some antennas have high-resolution ADCs and others have low-resolution ADCs. 2. It introduces two deep learning approaches - a direct-input deep neural network (DI-DNN) that takes all received signals as input, and a selective-input prediction DNN (SIP-DNN) that only uses signals from high-resolution ADCs to predict channels for all antennas. 3. The SIP-DNN aims to eliminate the impact of coarsely quantized signals from low-resolution ADCs on estimation accuracy by predicting channels based on
Detailed Information
| Author: | ['Tim Mazumdar'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 5 |
| Language: | English |
| Format: | |
| Price: | FREE |
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