Cooperative Sensing Assisted Joint Transmission for Ground-to-Air Communication Systems

Cooperative sensing and cooperative communications are viewed as promising techniques for improving the sensing and communication performance by utilizing the space diversity. In this paper, we investigate the cooperative-sensing assisted joint transmission for a ground-to-air system. By cooperatively processing the echoes from different UAVs, we propose a cooperative sensing scheme based on the extended Kalman filtering mechanism. To improve the system sum-rate based on the cooperative tracking information, we jointly optimize the transmit beam power of different BSs via a teaching-and- learning based optimization technique. Numerical results show that compared with the conventional separate sensing scheme, the proposed cooperative sensing scheme is able to significantly improve the positioning accuracy, thereby improving the communication performance.