Abstract
Satellite telecommunication systems promise to bridge digital gaps and deliver wireless communication services to any corner of the world. However, despite satellites’ global connectivity and wide footprint, still atmospheric and dust impairments are open challenges that face satellite systems, especially at high-frequency bands in arid and semiarid regions. Therefore, this paper aims to predict joint effects of atmospheric and dust attenuations in Gulf Cooperation Council (GCC) countries on CubeSat communications using Artificial Neural Network (ANN). The prediction model has been carried out using a massive Multiple-Input Multiple-Output (MIMO) antenna payload at K-frequency Bands. Consider these joint effects have positive relations in calculating satellites link margin, which leads to obtaining efficient communication system, delivering better quality of service (QoS), and enhancing Internet of Things (IoT) connectivity, or even Internet of Space Things (IoST). Predicated results infer that the ANN attenuation predictions, along with the 5G MIMO antenna on-board the CubeSat, offer much promise channel model for satellite communications, which in turn leads to not only supporting IoT connectivity but also reducing power consumption, thus enhancing lifetime of CubeSat. Also, this study can provide a reference for CubeSat engineers to guarantee large-capacity communication.
Highlights
Traditional wireless communication systems provide services with a good level of data rates, reconfigurable provision with various dynamic coverage demands. The deployment of these enabling technologies has led to a huge rise in the demand for mobile communications, partly due to the exponential growth in multimedia traffic and the emergence of a new type of technology such as the Internet of ings (IoT) or Big Data
One of those Artificial Intelligent (AI) techniques is an Artificial Neural Network (ANN), which is a computing system inspired by the biological neural networks that constitute biological brains, where all neurons contain individual weights and bias values that are parallel and organized nonlinear components
Carrier-to-noise ratio (CNR) of satellite links are evaluated at altitude of 600 km and 2 Ghz frequency band with wide consideration of atmospheric effects
Summary
Traditional wireless communication systems provide services with a good level of data rates, reconfigurable provision with various dynamic coverage demands. Carrier-to-noise ratio (CNR) of satellite links are evaluated at altitude of 600 km and 2 Ghz frequency band with wide consideration of atmospheric effects (gasses, rain, scintillation). But the work does not include high-frequency bands, where it truly shows the predictions of the atmospheric effects. Erefore, this paper aims to provide a comprehensive prediction model that encompasses joint effects of atmospheric and dust impairments from CubeSat communication aspect in the GCC region using ANN. Signals get attenuated as they pass by atmospheric effects, affecting the received signals at the ground users Services such as Internet connectivity and active or passive sensing can benefit from the strong received signal from the CubeSat side.
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