Optimal Binary Quantization and Detection for Distributed Sensing in Wireless Sensor Networks

This paper proposes a model-driven deep learning approach to optimize the binary quantizer at the sensors and the detector at the fusion center for distributed detection in wireless sensor networks, achieving near-optimal performance with reduced complexity.