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About 364 Power of Deep Learning For
Deep learning is proposed for channel estimation and signal detection in OFDM systems. A deep neural network model is trained offline using data from channel simulations to learn the characteristics of wireless channels. This trained model is then used online to directly recover transmitted data without additional training, unlike conventional methods that estimate channel state information first before detection. Simulation results show the deep learning approach achieves comparable performance to traditional methods when enough training pilots are available, and it can work better with limited pilots, cyclic prefix removal, and nonlinear noise. Deep learning is promising for addressing channel distortion and interference in wireless communications.
Detailed Information
| Author: | ['solarisan6'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 4 |
| Language: | English |
| Format: | |
| Price: | FREE |
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