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Found 5 papers, 1 papers with code
On the Implementation Complexity of Digital Full-Duplex Self-Interference Cancellation
In-band full-duplex systems promise to further increase the throughput of wireless systems, by simultaneously transmitting and receiving on the same frequency band.
Lupulus: A Flexible Hardware Accelerator for Neural Networks
Neural networks have become indispensable for a wide range of applications, but they suffer from high computational- and memory-requirements, requiring optimizations from the algorithmic description of the network to the hardware implementation.
Identification of Non-Linear RF Systems Using Backpropagation
In this work, we use deep unfolding to view cascaded non-linear RF systems as model-based neural networks.
Hardware Implementation of Neural Self-Interference Cancellation
In-band full-duplex systems can transmit and receive information simultaneously on the same frequency band.
Advanced Machine Learning Techniques for Self-Interference Cancellation in Full-Duplex Radios
For example, at a digital self-interference cancellation of 44. 51 dB, a complex-valued neural network requires 33. 7 % fewer floating-point operations and 26. 9 % fewer parameters compared to the polynomial model.
