Fixed Satellite Services (FSS) used to be alone at the C-Band spectrum in most countries. Since the deployment of 5G in many countries (i.e., 3.3–3.6 GHz), FSS is not the exclusive system in the C-Band anymore. In order to minimize the detrimental interference for the FSS to allowable levels, regional exclusion zones of maximum radiated power in 5G base stations (BS) are proposed and evaluated. In this paper, a measurement campaign has been carried out, and an analysis of the interference has been studied. A filtering model, namely Filter to Remove Broadband Interference 5G (FIREBRING), is proposed and analyzed concerning the carrier-to-noise ratio (C/N). Moreover, this paper focuses on the evaluation of the 5G interference into the FSS. The proposed solution deployed an Low-Noise Block (LNB) with a band frequency of 3.7 to 4.2 GHz to test the satellite down-conversion signal at the receiver. The paper offered a complete analysis of the 5G signal, taking into account the implications of out-of-band emissions, potentially LNB saturation into FSS receiver, and the repercussions of the deployment of the 5G BS active antenna systems. With the LNB and down-converter in place, it can be found that the signal interference between 1.450 GHz and 1.550 GHz, is nearly 18 dB.

This paper discusses the design and fabrication of a low-profile Hilbert-shaped metamaterial (MTM) array-based antenna, forming a rectangular patch with partial ground plane backing; the rest is slotted with traces for RF energy harvesting. The antenna is mounted on a 28 mm × 32 mm indium nickel oxide polymerized palm fiber (INP) substrate and compared to the identical one based on FR4 substrate. The two prototypes are printed with silver nanoparticles. Numerical and experimental tests are applied to the antenna performance in terms of S₁₁ and radiation patterns. The obtained antenna gain bandwidth product of the INP prototype is found to be significantly better than the FR4 prototype. The proposed INP antenna gain at 5.8 and 8 GHz frequencies is found to be about 4.56 and 7.38 dBi, respectively, while the FR4 antenna gain is found to be 4.56 and 6.85 dBi at 5.8 and 8 GHz, respectively. Finally, the resultant DC voltage and the efficiency of conversion from harvested RF energy are measured experimentally at 5.8 and 8 GHz for both proposed prototypes.

The Ka-band is modifying the mode of legacy communication towards versatile satellite-oriented systems with the beam-spot capability and a high-throughput architecture to provide twice the capability of classic Fixed Satellite Service (FSS) satellites, thus significantly reducing the cost per bit. Given this background, the contribution of precipitation rate and Ka-band downpour attenuation are expected to improve statistical models for effect prediction. The International Telecommunication Union (ITU) and local researchers are working tirelessly to determine the best prediction model for tropical climates. However, persistent and continuous efforts are required because currently available models do not perform well. The current prediction model for large datasets exhibits a certain deviation. Direct beacon measurement has been compared with an available prediction model that analyses rain effects in tropical regions. Theoretically, the size of the antenna and its gain influence the performance of the receiving signal. Size and availability are two factors which cause degradation and outage in the receiving signal. The majority of extant studies focus on a single antenna with a diameter lesser than 2.4m. Theoretically, antennas with a smaller diameter possess a smaller margin in comparison with antennas with larger diameters. This condition could affect the prediction model when the high attenuation causes a rapid outage in a small antenna and lead to the unavailability of measurement results. To study such effects and provide a good recommendation, the current work measures the beacon attenuation data at two locations, namely, Bukit Jalil (Kuala Lumpur) and Cyberjaya (Selangor). The locations are approximately 15 km apart and have antennas from 0.65m to 31.1m in sizes. Analyses using an available prediction model revealed that ITU-R P.618 provides the lowest RMS value of 14.37 with regards to rainfall rate on two selected samples in Malaysia. High-accuracy prediction can be achieved through the contribution of this study, and comparative data can be obtained for future research. This study is an encouraging step towards a highly comprehensive and accurate prediction of tropospheric impairments in Ka-band satellite communications in the tropical region.

Severe tropical weather dynamics impairments on the earth-sky signal quality at the Ku-band relative to temperate weather increase the demand for land mobile satellite (LMS) channel characterization and modeling specific to tropical regions. Variation in weather dynamics decreases the accuracy of the existing LMS channel models if applied to the tropics. This paper presents a tropical weather-aware LMS channel model that can be applied at areas with diverse atmospheric (rain, clouds, and tropospheric scintillation) and mobility impairments. The proposed tropical-LMS channel (TRO-LMSC) model is designed based on actual experimental measurements conducted in a tropical area. The TRO-LMSC model involves multipath design, mobility model, rain impairment model, cloud impairment model, tropospheric scintillation model, and link budget module (LBM). The proposed model shows improved channel modeling accuracy and comprehensiveness with relatively less root mean square error (rmse), compared with existing models. Consequently, this improvement enhances the identification of the type and performance of the fade mitigation technique, the management of available communication resources, and the reliability and efficiency of the communication services.

Rain attenuation poses a significant challenge for high-throughput communication systems. In response, this paper introduces an artificial intelligence (AI) model designed for predicting and mitigating rain-induced impairments in high-throughput satellite (HTS) to land channels. The model is based on three AI algorithms developed using 3D antenna design to characterize, analyze, and mitigate rain-induced attenuation, optimizing channel quality specifically in the United Arab Emirates (UAE). The study evaluates various parameters, including rain-specific attenuation, effective slant path through rain, rain-induced attenuation, signal carrier-to-noise ratio, and symbol error rate, for five conventional modulation schemes: Quadrature Phase-Shift Keying (QPSK), 8-Phase Shift Keying (8-PSK), 16-Quadrature Amplitude Modulation (16-QAM), 32-QAM, and 64-QAM. Additionally, the paper introduces a new database detailing rain-induced attenuation in HTS channels in the UAE at different frequencies using measured rainfall intensities. The paper concludes by proposing a smart antenna design with a frequency diversity technique for fade mitigation. Results indicate that rain-induced attenuation varies significantly based on rainfall rate and frequency. Specifically, at 25 GHz and a rainfall rate of 100 mm/h, the rain-induced attenuation can reach as high as 15 dB, resulting in a significant decline in signal quality and link performance. The proposed AI model demonstrates the ability to intelligently predict rain-induced attenuation and channel quality for various rainfall rates and frequencies. This information can be valuable for optimizing satellite link design and operation, ultimately enhancing the reliability and quality of satellite communications. The proposed two-slot smart antenna design utilizes frequency diversity to effectively mitigate rain attenuation, contributing to the overall improvement of link reliability and quality.