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A Reverse Jensen Inequality Result with Application to Mutual Information Estimation
The Jensen inequality is a widely used tool in a multitude of fields, such as for example information theory and machine learning.
Explicit CSI Feedback Compression via Learned Approximate Message Passing
Explicit channel state information at the transmitter side is helpful to improve downlink precoding performance for multi-user MIMO systems.
Reinforce Security: A Model-Free Approach Towards Secure Wiretap Coding
The use of deep learning-based techniques for approximating secure encoding functions has attracted considerable interest in wireless communications due to impressive results obtained for general coding and decoding tasks for wireless communication systems.
ComPass: Proximity Aware Common Passphrase Agreement Protocol for Wi-Fi devices Using Physical Layer Security
Secure and scalable device provisioning is a notorious challenge in Wi-Fi.
Cryptography and Security
Using AoI Forecasts in Communicating and Robust Distributed Model-Predictive Control
By contrast, the present approachestablishes a robust distributed model-predictive controlscheme, in which the local subsystem controllers oper-ate under the assumption of a variable communicationschedule that is predicted by a network controller.
Systems and Control Systems and Control
Deep Learning for Channel Coding via Neural Mutual Information Estimation
However, one of the drawbacks of current learning approaches is that a differentiable channel model is needed for the training of the underlying neural networks.
Compressive Estimation of a Stochastic Process with Unknown Autocorrelation Function
To design such a blind predictor, we use the random spectral representation of a stationary Gaussian process.
