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Sporadic E (Es) layers are thin enhanced ionization patches. The electron density of Es layer is very high, up to 100 times that of the regular E layer. Therefore, Es layer has a significant effect on radio wave propagation. The formation mechanisms of Es layers is very complicated, so it needs multi-observations and simulations research. Combined observations using an ionosonde, very high frequency (VHF) coherent backscatter radar, VHF broadband backscatter radar, and meteor radar were performed. The height and irregular structure of mid-latitude Es layers observed by ionosonde, VHF coherent backscatter radar and VHF broadband backscatter radar were compared with the zonal and meridional winds observed by meteor radar, the role of wind shear on the formation of Es layer was confirmed, and examples were also found where wind shear theory could not explain and apply to the formation of Es layer. We simulated the formation of Es layers based on wind shear theory. The results of simulations and observations revealed other potential role for Es layer formation besides wind shear. By comparing the height of turbopause with that of Es layer, it was found that the variation of the altitudes of turbopause and Es layer was consistent over different latitude stations, and the effect of the turbopause on the formation of Es layer was proposed. The combined effects of eddy diffusion below and molecular ion collision above turbopause can prevent metal ions from drifting downward and promote their convergence to form thin plasma layers at the turbopause height. The turbopause accumulation effect is considered as a potentially important mechanism for the formation of Es layers besides wind shear theory. The study in the paper is helpful for analysis of physical origin and modeling of Es layer. [ABSTRACT FROM AUTHOR]

In this paper, aiming at the spectrum coexistence scenario between non-geostationary satellite orbit (NGSO) and geostationary satellite orbit (GSO) satellite systems, the NGSO network, a secondary system, reuses the spectrum resources of the GSO primary system through spectrum sensing and sharing technology. Combined with the influence of factors such as the radio wave propagation model and channel characteristics of the sensing links, as well as the difference of channel environment between sensing nodes, a weighted cooperative spectrum sensing strategy named optimal fusion decision for time-invariant channel link (OFD-TIC) method was proposed for NGSO–GSO downlink sensing communication. The OFD-TIC method is designed to minimize the global error detection probability while considering the constraints of spectrum conflict probability and false alarm probability. To achieve this, OFD-TIC method transforms the optimization problem into a Lagrange function and utilizes Newton's iterative method to obtain the weights of sensing node and the parameter thresholds for fusion decision. In the six different spectrum sensing scenarios constructed using satellite network data registered by the International Telecommunication Union (ITU), the performance evaluation of the proposed OFD-TIC method is carried out and the simulation results demonstrate that the proposed method outperforms existing typical algorithms. Under the same signal-to-noise ratios (SNR) and sampling number, the OFD-TIC strategy achieves a higher global detection probability than others. Furthermore, the proposed method exhibits fast convergence to 1 of the global detection probability even at low SNR. [ABSTRACT FROM AUTHOR]

This paper focuses on the characterization of radio propagation, and data communication in a marine environment. More specifically, we consider signal propagation when three different sub-gigahertz industrial, scientific, and medical (ISM) bands, i.e., 169 MHz, 434 MHz, and 868 MHz, are used. The main focus of the paper is to evaluate the path loss (PL), i.e., the power loss that a propagation radio wave would experience when communication occurs between a sail boat and a buoy. We describe the measurement results obtained performing three different radio power measurement campaigns, at the three different aforementioned ISM sub-gigahertz bands. We also want to correlate the radio propagation quality with the weather conditions present in the measurement areas. The obtained results show that higher distances are achieved by transmitting at lower frequencies, i.e., 169 MHz, and, on average, the propagation is directly dependent from the dew point index. [ABSTRACT FROM AUTHOR]

The graph neural network (GNN) has shown outstanding performance in processing unstructured data. However, the downstream task performance of GNN strongly depends on the accuracy of data graph structural features and, as a type of deep learning (DL) model, the size of the training dataset is equally crucial to its performance. This paper is based on graph neural networks to predict and complete the target radio environment map (REM) through multiple complete REMs and sparse spectrum monitoring data in the target domain. Due to the complexity of radio wave propagation in space, it is difficult to accurately and explicitly construct the spatial graph structure of the spectral data. In response to the two above issues, we propose a multi-source domain adaptive of GNN for regression (GNN-MDAR) model, which includes two key modules: (1) graph structure alignment modules are used to capture and learn graph structure information shared by cross-domain radio propagation and extract reliable graph structure information for downstream reference signal receiving power (RSRP) prediction task; and (2) a spatial distribution matching module is used to reduce the feature distribution mismatch across spatial grids and improve the model's ability to remain domain invariant. Based on the measured REMs dataset, the comparative results of simulation experiments show that the GNN-MDAR outperforms the other four benchmark methods in accuracy when there is less RSRP label data in the target domain. [ABSTRACT FROM AUTHOR]

Today's network is continuously evolving through a variety of wireless communication systems. Wireless communication is now available just about anywhere--it has become an integral part of everyday life and brought us many benefits. At the same time, wireless communication is predicted to become increasingly complex in the future, so there is a need for further evolution of the wireless network to deal with this complexity. NTT Distinguished Researcher Motoharu Sasaki says, "It is important that the network be easy for people to use without having to think about it." In this article, we talk with him about his activities as a rising researcher including his research on "achieving complete wireless communication through estimation and prediction technology for radio wave propagation characteristics." [ABSTRACT FROM AUTHOR]

Transionospheric radio signals might undergo random modulations of their amplitude and phase caused by scattering on irregular structures in the ionosphere. These scintillation phenomena are highly anisotropic, depend on local geomagnetic field configuaration and on the relative position of the signal receiver and scattering irregularity. We derive analytical expressions of anisotropic amplitude and phase scintillation indices using the model of a thin random phase screen. These results extend the classical derivations of [C. Rino, Radio Sci. 14 , 1135 (1979)] to a larger domain of applicability including very slant propagation links of the radio wave signals. The derived generalization is based on the assumption that the ionospheric scattering layer has a spherical symmetry as opposed to the original Rino's assumption of a plan-parallel ionospheric layer. The derived scintillation indices have the simpler analytical form, determine the regions of enhanced scintillation by taking into account the finite curvature of the Earth and of the ionospheric shell, and are divergence-free for large zenith angles of propagation links. For the illustration we discuss the geometric enhancement of scintillation for communication links via a geostationary beacon satellite over the equator. [ABSTRACT FROM AUTHOR]

In this paper, the urban signal propagation characteristics based on the location of blind sources are investigated. To address the issue of blind electromagnetic radiation sources in complex urban environments, intelligent methods for propagation channel path classification, and model determination are brought forth based on field test data. The intelligent classification method distinguishes between the Line-of-Sight (LoS) path channel and a direct path, the LoS multipath channel with a direct path and other multiple paths, and the Non-Line-of-Sight (NLoS) multipath channel without a direct path from the source to the test point. The modeling aspect determines the model type to which the received signal belongs based on the statistical model derived from the tested data of a specific source. A validation measurement system was constructed for the FM broadcasting band, and validation campaigns were conducted in the city of Wuhan. The process and analysis of the data using this method demonstrate the accurate distinction of the different propagation path channels and models and involve the construction of a statistical model for the FM band in Wuhan's urban area. [ABSTRACT FROM AUTHOR]

Mobile communication base stations have become ubiquitous with the popularization and development of mobile communication services. Although the Chinese government has designated a radio quiet zone (RQZ) specifically for Five-hundred-meter Aperture Spherical radio Telescope (FAST), the 4G International Mobile Telecommunications (4G-IMT) system is still heavily used to meet the communication needs around the RQZ. To assess the Electromagnetic Interference (EMI) caused by 4G-IMT base stations on the performance of FAST, this paper employs the International Telecommunication Union (ITU) deterministic radio wave propagation prediction model. The interference of 4G-IMT base stations on FAST is evaluated based on relevant parameters, such as the frequency used by both FAST and the base station, in conjunction with the FAST threshold protection requirements. The results indicate that 47.73 % of the data exceed the radio astronomy protection threshold of FAST. In addition, a field experiment was conducted to verify the accuracy of the radio wave propagation prediction method used. The root-mean-square error between the predicted value and the measured value was found to be 6.94 dB, supporting the accuracy of the predicted results. The findings of this study can help suppress interference from mobile communication services around the RQZ of FAST and optimize the electromagnetic environment around FAST. [ABSTRACT FROM AUTHOR]

Numerical modeling of primary cosmic ray protons' transport through the Earth's atmosphere was performed for the energy spectra of solar energetic particle events (SEPs). Several events in the last three solar cycles were considered. A comparative analysis of the characteristics of coronal mass ejections and primary proton fluxes was carried out. The main results were quantitative estimates of the calculated atmospheric ionization count rate for a wide range of altitudes (from sea level up to 98 km). The difference in the influence of solar protons on the Earth's atmosphere is considered for seven SEPs divided into three groups with similar solar sources (X-flare magnitude and coordinates) but with different characteristics of accelerated particle fluxes. The data obtained in this work are very important for future studies of radio wave propagation, atmospheric chemistry and climate change. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for extracting the structure of an indoor environment using radar. When using the radar in an indoor environment, ghost targets are observed through the multipath propagation of radio waves. The presence of these ghost targets obstructs accurate mapping in the indoor environment, consequently hindering the extraction of the indoor environment. Therefore, we propose a deep learning-based method that uses image-to-image translation to extract the structure of the indoor environment by removing ghost targets from the indoor environment map. In this paper, the proposed method employs a conditional generative adversarial network (CGAN), which includes a U-Net-based generator and a patch-generative adversarial network-based discriminator. By repeating the process of determining whether the structure of the generated indoor environment is real or fake, CGAN ultimately returns a structure similar to the real environment. First, we generate a map of the indoor environment using radar, which includes ghost targets. Next, the structure of the indoor environment is extracted from the map using the proposed method. Then, we compare the proposed method, which is based on the structural similarity index and structural content, with the k-nearest neighbors algorithm, Hough transform, and density-based spatial clustering of applications with noise-based environment extraction method. When comparing the methods, our proposed method offers the advantage of extracting a more accurate environment without requiring parameter adjustments, even when the environment is changed. [ABSTRACT FROM AUTHOR]

Radio wave propagation modelling in railway environments is of fundamental importance in designing reliable train communication systems. Parabolic equation (PE) methods have been widely applied to the modelling of wave propagation in tunnels due to their high computational efficiency and fidelity. The finite-difference parabolic equation (FDPE) and the split-step parabolic equation (SSPE) methods are two commonly used approaches to solve PE numerically. However, the relevant literature is still missing a comprehensive study of their performance, including the selection of parameters such as discretisation steps and the tradeoffs involved in terms of their accuracy and efficiency, especially as current wireless systems shift to high frequencies. In this study, a systematic analysis of the error and computational complexity of the FDPE and SSPE methods for radio wave propagation modelling in tunnels is provided. Guidelines for the choice of their parameters are provided, and their performance is demonstrated through both numerical examples and experimental measurements in actual tunnel cases. [ABSTRACT FROM AUTHOR]

Vertical radio refractivity gradients are essential for monitoring propagation conditions when designing and planning terrestrial radio links for communications in the lower atmosphere. Average data gathered from meteorological factors such as temperature, pressure, and relative humidity was used from 1980 to 2020 n this study. This study focuses on the vertical gradient of radio refractivity within the lower atmospheric layer, investigating its influence on factors like signal propagation, route clearance, and line-of-sight communication. The analysis encompasses three cities - Abuja, Makurdi, and Jos. In Figure 2 monthly average changes in the refractivity gradient are presented for Abuja. In addition, the seasonal radio refractivity gradient shows mean values of -110.000N/km for Abuja which shows that the refractivity condition is Super-Refraction, -77.553N/km for Jos which shows that the refractivity condition is Normal-Refraction and - 97.209N/km for Makurdi which shows that the refractivity condition is Normal-Refraction respectively. Higher gradient values, G1, G2, and G3 were observed during the dry season (December-February) which could be attributed to dry air and steeper refractivity gradients. In contrast, lower gradient values were observed during the wet season (June-October) due to increased atmospheric moisture. Similarly, measured vertical radio refractivity gradient data, G1 N/km, G2 N/km, and G3 N/km for Jos displayed consistent fluctuations throughout the year. Similarly, measured vertical radio refractivity gradient data, G1 N/km, G2 N/km, and G3 N/km for Jos displayed consistent fluctuations throughout the year. Notably, wetter months exhibit higher refractivity gradient values, while drier months show lower values. G2 consistently records the highest gradient values, and despite varying magnitudes, the trends remain consistent. Finally, measured vertical radio refractivity gradient data, G1 N/km, G2 N/km, and G3 N/km for Makurdi indicate distinct fluctuations with the most negative values observed in November and December. The Dry Season witnesses relatively lower gradient values, while the Transition and Wet Seasons experience rising values, influenced by atmospheric shifts. The Higher negative values during the wet season suggest pronounced variations in the refractive index, affecting radio wave propagation. These findings emphasize the significance of refractivity gradient variations and their implications for radio wave behaviour particularly during different seasons. [ABSTRACT FROM AUTHOR]

Parabolic equations (PE) are commonly employed for calculating the spatial propagation loss of wireless signals. The initial field is a crucial factor. To investigate the impact of construction accuracy on the calculation of radio wave propagation loss, we selected the half-wave dipole antenna and its Gaussian approximation to examine the influence of wide-angle PE modeling. We analyzed the disparities between the actual antenna pattern and the Gaussian beam approximation, as well as the discrepancies in the corresponding initial field and the calculation of radio wave propagation loss in PE modeling. The simulation results indicate that the error of the Gaussian approximation increases as the angle of departure from the antenna main beam increases, with a relative error of approximately 30% in the initial field. A comparison between the experimental test of the broadcast signal and the simulation calculation reveals that the model based on the actual antenna aligns more closely with the measured value on a flat underlying surface. However, in mountainous areas with significant fluctuations, the simulation results are consistent with each other and higher than the measured value. The inversion results obtained through the particle swarm optimization algorithm demonstrate that the model based on the actual antenna exhibits superior inversion accuracy for the tropospheric atmospheric duct structure. [ABSTRACT FROM AUTHOR]

The document is a notice board from the Journal of the British Astronomical Association. It provides information about upcoming astronomical meetings and events. The meetings include the BAA One Day Spring Meeting, the BAA Radio Astronomy Section Webinar, the BAA Historical Section Meeting, the BAA Winchester Weekend, and the BAA Meeting. The document also mentions the availability of free items related to astronomy. [Extracted from the article]

In this paper, to investigate the problem of radio wave propagation in complex environments, a new algorithm is proposed based on the equivalence principle algorithm and the domain decomposition method to rapidly and accurately predict electromagnetic scattering and radio wave propagation in half-space. First, equivalent surfaces are introduced to decompose the obstacle region and replace the scattering effect of obstacles within the equivalent surfaces with equivalent input and output electromagnetic currents. Then, the operator S, representing the relationship between the input and output equivalent electromagnetic currents on the equivalent surfaces, and the operator T, representing the interactions between the equivalent electromagnetic currents on each equivalent surface, are derived; this allows the calculation process of the overall spatial field in a complex environment to be simplified to the iterative calculation process of operators S and T. To reduce the complexity of calculating S, a neural network embedded with physical information is introduced to replace the calculation process. Finally, the training results are applied to an example and compared with the theoretical numerical results yielded by the method of moments in different cases with obstacles. The results reveal that the new method proposed in this paper is highly accurate and achieves a substantial improvement in calculation speed. Therefore, our proposed algorithm provides a new and reliable method for calculating the spatial field in complex environments. • The EPA is introduced to use equivalent surfaces to replace the scattering inside it. • The operators S and T are introduced into the process of solving the field. • A neural network with physical information embedded is applied to calculate the S. • Random undulating terrains are generated by Karhunen–Loève expansion. • MoM providing a good foundation for training is used to generate dataset. [ABSTRACT FROM AUTHOR]