CROWN: Channel Responsive Operational Waveform for Airborne Networks

Current modular approaches to generate a waveform has led to efficient, versatile, and controllable communication systems that we have today with individually optimized processing blocks. However, this individual optimization process does not necessarily optimize the overall end-to-end communication system. Moreover, these designs are either channel agnostic or rely on accurate channel models and precise channel distribution assumptions. As a result, they do not meet the performance expectations for airborne, i.e., UAV, communications with very dynamic and complex channel environment and hardware impairments, and fall short of realizing the potential benefits of airborne communications. Intelligent Automation, Inc. (IAI) proposes to develop the Channel Responsive Operational Waveform for Airborne Networks (CROWN) solution which will generate channel and interference-aware waveforms optimized for airborne (such as UAV) networks. We will represent both the transmitter and receiver as deep neural networks, and jointly train them while taking the hardware impairments and airborne network channel and interference effects into account. We will evaluate the performance of the developed algorithms using simulations and hardware-in-the-loop network channel emulation tests.