Auto-Encoder Learning-Based UAV Communications for Livestock Management

The advancement in computing and telecommunication has broadened the applications of drones beyond military surveillance to other fields, such as agriculture. Livestock farming using unmanned aerial vehicle (UAV) systems requires monitoring animals on relatively large farmland. A reliable communication system between UAVs ground control station (GCS) is necessary achieve this. This paper describes learning-based strategies techniques that enable interaction data exchange a GCS. We propose deep auto-encoder UAV design framework for end-to-end communications. Simulation results show learns joint transmitter receiver mapping functions various strategies, QPSK, 8PSK, 16PSK 16QAM, without prior knowledge.