Multi-layer MIMO Relay as Deep Physical Neural Networks: Power Amplifiers as Activation Functions
Researchers propose a deep wireless physical neural network (WPNN) architecture where nonlinear activations are implemented using the intrinsic nonlinearities of power amplifiers in a multi-hop MIMO relay network. The system forms an over-the-air, fully connected network trainable end-to-end, with two transceiver designs tailored for different channel state information (CSI) scenarios. Simulations demonstrate accurate over-the-air image classification, showing the potential of leveraging hardware nonlinearity for neural computation.
Why it matters: This work presents a novel method for embedding neural computation directly into analog wireless hardware, which could enable more energy-efficient and lower-latency AI inference at the network edge.
Full story at: arXiv Machine Learning ↗