Compressed Robust Transmission for Remote Sensing Services in Space Information Networks

Abstract

With rapid development of space platforms such as small satellites and UAVs for public services, remote sensing services have been considered as one of the most promising services in space information networks. Small satellites and UAVs equipped with sensors such as cameras capture on-demand images and videos. Various remote sensing services using these images and videos can be enabled for public users, including geographical photography, navigation, live broadcast, surveillance and monitoring, road traffic analysis, and so on. In these remote sensing services, images and videos must be transmitted to individual users in a real-time manner. Therefore, the transmission techniques adopted will have direct impact on the received quality of users. As a newly emerged robust wireless transmission scheme, Soft- Cast is able to accommodate multiple receivers of different channel conditions by directly transmitting power scaled samples. In this article, CS and robust transmission-based SoftCast are investigated for downlink image/video-based remote sensing services under resource-limited, time-varying, and heterogeneous space environments, which are developed in order to improve bandwidth utilization efficiency and to achieve graceful performance, respectively. The proposed ComCast scheme is implemented by integrating CS and robust transmission into one framework to exploit benefits from both techniques. Furthermore, resource allocation in ComCast is also addressed to minimize system distortion caused by both CS and transmission. Simulation results demonstrate that ComCast outperforms the existing CS-based scheme as well as the robust transmission scheme in terms of peak signal-to-noise ratio and visual quality.