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· 1 hour

Deep Learning Based 5G Channel Estimation: Design to FPGA Deployment

Monday, January 25, 2021 · 10:52 a.m. · Eastern Time (US & Canada)
Note: This webinar is part of a multi-session recurring webinar: Deep Learning Based 5G Channel Estimation: Design to FPGA Deployment.
About This Webinar

Performance expectation from the 5G wireless system surpasses the capability of conventional methodologies. There is an exponential increase in system complexity due to advanced algorithm design, which results in a pressing need for higher estimation precision and reduction in the design complexity. 

Deep learning is powering a massive shift in the roles that computers play in our personal and professional lives. Most technical organizations expect to gain or strengthen their competitive advantage of using deep learning. Deep learning and machine learning are transforming industries with high impact. The wireless communication industry is no exception. 

In this demo we replace the practical 5G channel estimator with trained CNN. As a part of this demo, you will be able to understand the complete deep learning workflow, which includes: 

• Using data synthesis techniques to train deep learning and machine learning networks for a range of wireless communications systems 
• Understanding dataset tradeoffs between CNN architectures
• Validating the AI models
• Deploying the model on FPGA

Channel estimators are required by wireless nodes to perform essential tasks such as precoding, beamforming, and data detection. They estimate the distortion of the signal between the transmitter and the receiver. As for many use cases, the motivation to use AI here is to achieve higher estimation precision and reduction in the design complexity.  

This demo highlights the workflow to build such a solution for a simple SISO system and a narrow range of SNR, while in practice AI may be applied to more complex systems using mmWave massive MIMO architectures. This is where the challenges associated with channel estimation will be the more visible. 

The benefits of this demo for the customers are the following: 
• Understand how AI can be applied to tackle 5G physical layer challenges 
• Highlight how a non-AI expert could build an optimized AI algorithm in MATLAB 
• Show how to rapidly move from building an AI algorithm to prototyping on FPGA devices with limited hardware knowledge

The targets for this demo are engineering teams working on wireless physical layer design/optimization problems. This demo explains the application of deep learning for the 5G channel estimation. The same idea can be leveraged to larger scope of wireless problem statements across various layers and technologies. 

Who can view: Everyone
Webinar Price: Free
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