Abstract:
The rain attenuation affects the availability of the Ground Segment network, impacting mainly to the satellite links. The gateway station feeder uplink works in Q/V band,...Show MoreMetadata
Abstract:
The rain attenuation affects the availability of the Ground Segment network, impacting mainly to the satellite links. The gateway station feeder uplink works in Q/V band, which turns into very susceptible to weather impairments. This means that it is inactive when the feeder link is affected by a rain fading event. Therefore, we propose learning methods to improve a network scheme being capable of ensuring high availability and reducing the number of redundant gateways on the ground segment. These methods are based on machine learning techniques that are adequately implemented in our system model. Finally, we evaluate the performance of the system model to demonstrate that our implementation provides high availability and an optimal number of redundant gateways.
Date of Conference: 25-28 February 2020
Date Added to IEEE Xplore: 16 April 2020
ISBN Information: