Site Diversity Switching Prediction AT Q Band Using Deep Learning Techniques in Satellite Communications

An efficient deep learning (DL) architecture for switching prediction in site diversity schemes for Q band (39.402GHz) links is presented. The paper proposes the implementation of a DL detector (D) model in each station, that raises a flag when a rain event occurs, exploiting the benefits of transformer networks. When the event is detected, a DL regressor (R) model is triggered to predict future attenuation values for the specific event in each station. Both detector and regressor models consist of attention mechanisms that identify temporal dependencies between the input sequence elements. The experimental evaluation along with state of the art techniques indicate promising results.

[1]  A. Z. Papafragkakis,et al.  Excess Attenuation Detection in Satellite Communication Channel Measurements with Deep Learning Architectures , 2023, 2023 17th European Conference on Antennas and Propagation (EuCAP).

[2]  A. D. Usman,et al.  A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction , 2022, Sustainability.

[3]  Christos N. Efrem,et al.  Capacity Allocation Mechanisms in High-Throughput Satellite Systems: One-to-Many Pairings , 2022, IEEE Systems Journal.

[4]  Huibin Wang,et al.  A new multiple gateway transmit diversity technique for future satellite networks , 2022, China Communications.

[5]  F. Marzano,et al.  Short-term Forecast of Radiocommunication Geostationary Satellite Links coupling Weather Prediction and Radiopropagation Models , 2022, 2022 16th European Conference on Antennas and Propagation (EuCAP).

[6]  Flor G. Ortiz-Gomez,et al.  Method of Rain Attenuation Prediction Based on Long–Short Term Memory Network , 2022, Neural Processing Letters.

[7]  Charilaos I. Kourogiorgas,et al.  An Optimized Simple Strategy for Capacity Allocation in Satellite Systems With Smart Gateway Diversity , 2021, IEEE Systems Journal.

[8]  Apostolos Z. Papafragkakis,et al.  Site-Diversity Ka-Band Satellite Propagation Campaign in Attica, Greece, Using Alphasat: First 2 Years' Results , 2019, IEEE Antennas and Wireless Propagation Letters.

[9]  Antonio Martellucci,et al.  Assessment of spatial and temporal properties of Ka/Q band earth‐space radio channel across Europe using Alphasat Aldo Paraboni payload , 2019, Int. J. Satell. Commun. Netw..

[10]  T. Tjelta,et al.  Three-Site Diversity at Ka-Band Satellite Links in Norway: Gain, Fade Duration, and the Impact of Switching Schemes , 2017, IEEE Transactions on Antennas and Propagation.

[11]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[12]  Laurent Castanet,et al.  Tropospheric propagation forecasts for smart gateways switching algorithms , 2016, 2016 8th Advanced Satellite Multimedia Systems Conference and the 14th Signal Processing for Space Communications Workshop (ASMS/SPSC).

[13]  Björn E. Ottersten,et al.  Gateway Switching in Q/V Band Satellite Feeder Links , 2013, IEEE Communications Letters.

[14]  Mohamed-Slim Alouini,et al.  Markov chains and performance comparison of switched diversity systems , 2004, IEEE Transactions on Communications.

[15]  Panayotis G. Cottis,et al.  Satellite communications at KU, KA, and V bands: Propagation impairments and mitigation techniques , 2004, IEEE Communications Surveys & Tutorials.

[16]  Xiang Cheng,et al.  An Atmosphere Data Driven Q Band Satellite Channel Model with Feature Selection , 2021, IEEE Transactions on Antennas and Propagation.

[17]  M. Bousquet,et al.  INTERFERENCE AND FADE MITIGATION TECHNIQUES FOR KA AND Q/V BAND SATELLITE COMMUNICATION SYSTEMS , 2022 .