The evolution of communication system to the next generation e.g. B5G and 6G demands an ultra-reliable performance regardless of weather conditions. Such ultra-reliable system design will require that that the effects of short-term adverse weather events on communication system has to be modelled more accurately so that system design should be dynamically adaptive to such events. The performance of satellite link is severely affected by dynamic rain attenuation and thus an accurate and reliable modelling of performance parameters is essential for dynamic fade countermeasures especially above 10 GHz. In this work, we model the energy per bit to noise spectral density ratio ($E_b/N_0$) using Gaussian Mixture (GM) model during rainy events. The developed mathematical expression is used to accurately model the bit error rate (BER), outage probability and channel capacity of the link. The average BER, upper bound on BER and average ergodic capacity of an M-ary phase shift keying scheme (MPSK) using the GM model of $E_b/N_0$ is derived to evaluate the performance of the link under such short-term weather impairments. We then show the numerical results and analysis using the GM model of the measured $E_b/N_0$ data obtained with AMoS-7 satellite at a site located in Israel.

The received signal at the ground station for a satellite link is affected by the stochastic nature of atmospheric channel. Adverse weather events such as rain not only attenuates the signal but also increases noise, scintillation fading and multipath effects that cause rapid variations in the received signal at the ground station. In order to analyze the stochastic effects of weather phenomenon on the link performance on short-term basis, both the slowly changing signal attenuation and the rapid variations caused by channel at the receiver has to be studied. In this work, we first analyze the short-term effects of rain on the statistical and spectral properties of fast varying signal component affecting the link performance. Following this, we model such parameters using several features extracted from the slowly varying signal component with support vector machine (SVM). We show an interesting result that the statistical and spectral properties of fast varying signal under rainy channel conditions can be predicted with very high accuracy using SVM. The prediction of such parameters will lead to receiver design adaptive to varying channel dynamics affecting the link performance under rainy conditions.

The progress in quantum computing would make the traditional encryption methods easier to hack and hence the next generation of communication networks should include various cross-layer solutions to ensure the cybersecurity of network. In this work, we propose a physical layer solution that rely on taking advantage from the inherent physical properties of the channel that marks its imprint on the propagation of the electromagnetic signal through the stochastic atmospheric channel. The proposed architecture would ensure the cybersecurity of a ground station against an MITM attack launched from an aerial platform (AP). As the signal traverses through the channel, various atmospheric effects including thermal noise and tropospheric scintillation fading causes rapid fluctuations in the received signal. The signal at the ground station from a satellite and an AP would traverse different spatial path over the dynamic atmosphere and hence will show different noise like rapid variations at the ground station. These noisy variations are extracted from the received signal using wavelet filtering technique and processed through a deep neural network based on long-short term memory network (LSTM) to identify whether the incoming signal belong to a legitimate satellite or a spoofing AP. We show that an accuracy of more than $98 \%$ is achieved in the considered scenario with the proposed network architecture as the altitude of AP changes for launching a machine-in-the-middle (MITM) attack in the line-of-sight direction.

The increasing demand in data rates and new emerging applications require that the future generation of satellite networks will be designed at sub-THz frequencies with ultra-broad bandwidth. At such frequencies, the satellite channel is impaired by the highly frequency dependent absorption of the signal by the gaseous atmospheric media besides the thermal noise from the sky, the ground, receiver circuit and molecular absorption noise thus, making it a highly frequency-selective channel. In this work, we derive a theoretical upper bound on the channel capacity of a LEO satellite communication link by optimizing the power spectral density (PSD) of the transmitted signal considering the physicla aspects of THz channel. We obtain a closed form expression of optimum transmitted signal PSD that maximizes the channel capacity of LEO satellite link as the elevation angle changes with the transmitted power held constant.