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Found 5 papers, 0 papers with code
Semi-Supervised Learning via Swapped Prediction for Communication Signal Recognition
Deep neural networks have been widely used in communication signal recognition and achieved remarkable performance, but this superiority typically depends on using massive examples for supervised learning, whereas training a deep neural network on small datasets with few labels generally falls into overfitting, resulting in degenerated performance.
Radio Generation Using Generative Adversarial Networks with An Unrolled Design
Experimental results with extensive simulations demonstrate that our proposed GAN framework can effectively learn transmitter characteristics and various channel effects, thus accurately modeling for an underlying sampling distribution to synthesize radio signals of high quality.
Open-Set RF Fingerprinting via Improved Prototype Learning
Deep learning has been widely used in radio frequency (RF) fingerprinting.
Semi-Supervised RF Fingerprinting with Consistency-Based Regularization
As a promising non-password authentication technology, radio frequency (RF) fingerprinting can greatly improve wireless security.
Environment-Aware Codebook for Reconfigurable Intelligent Surface-Aided MISO Communications
Reconfigurable intelligent surface (RIS) is a revolutionary technology that can customize the wireless channel and improve the energy efficiency of next-generation cellular networks.
