Radio climatology of Rajasthan

Based on 30-year averages of the values of atmospheric pressure, temperature and vapour pressure near the ground surface, value's of radio refractive indices for 18 stations of Rajasthan State and adjoining area near and within international border line, have been computed. Using these data, monthly and annual distributions of radio refractive indices over the area for both morning and evening have been describe-d and discussed which may be useful in radiowave propagation in the area.

An evaluation of Quasi-Moment-Method calibrated pathloss models for Benin City Nigeria

This paper introduces the Quasi-Moment-Method (QMM) as a novel radiowave propagation pathloss model calibration tool, and evaluates its performance, using field measurement data from different cellular mobile communication network sites in Benin City, Nigeria. The QMM recognizes the suitability of component parameters of existing basic models for the definition of ‘expansion’ and ‘testing functions’ in a Galerkin approach, and simulations were carried out with the use of a FORTRAN program developed by the authors, supported by matrix inversion in the MATLAB environment. Computational results reveal that in terms of both Root Mean Square (RMS) and Mean Prediction (MP) errors, QMM-calibrated models performed much better than an ‘optimum’ model reported for the NIFOR (Benin City), by a recent publication. As a matter of fact, the QMM-calibrated COST231 (rural area) model recorded reductions in RMS error of between 31.5% and 71% compared with corresponding metrics due to the aforementioned ‘optimum’ model. The simulation results also revealed that of the five basic models (COST231-rural area and suburban city, ECC33 (medium and large sized cities), and Ericsson models) utilized as candidates, the two ECC33 models, whose performances were consistently comparable, represented the best models for QMM-model calibration in the Benin City environments investigated.

Perencanaan Jaringan 4G LTE 1800 MHz In-building pada Fakultas Kedokteran UM-Palembang menggunakan Propagasi COST-231

Perencanaan jaringan telekomunikasi merupakan hal yang sangat menentukan dalam kualitas sinyal pada jaringan yang diterima oleh pelanggam. Permasalahan yang sering terjadi adalah kualitas level sinyal coverage yang tidak merata terutama pada kondisi dalam gedung (Indoor). Sehingga kondisi dalam bangunan memerlukan perancanaan khusus untuk memastikan kondisi kualitas sinyal agar tidak terdapat blank spot. Pada penelitian ini merencanaan jaringan indoor 4G LTE frekuensi 1800 MHz dengan menggunakan model propagasi COST-231 pada gedung Laboratorium Fakultas Kedokteran Universitas Muhammadiyah Palembang. Penelitian ini menggunakan software radiowave propagation simulator. Hasil dari penelitian ini yaitu dengan perbedaan power transmit (2 antenna vertikal) menunjukkan bahwa semakin tinggi nilai power transmit, maka nilai RSRP semakin baik. Akan tetapi nilai power transmit tidak mempengaruhi baik atau buruknya kualitas sinyal SIR.Pada analisa jumlah antenna yaitu 2 antenna, 3 anntena dan 4 antenna menunjukkan bahwa semakin banyak antenna yang digunakan pada gedung, maka nilai RSRP akan semakin baik, akan tetapi nilai SIR akan semakin jelek karena efek Interferensi antar antenna.

Towards Physics-Based Generalizable Convolutional Neural Network Models for Indoor Propagation

A fundamental challenge for machine learning models for electromagnetics is their ability to predict output quantities of interest (such as fields and scattering parameters) in geometries that the model has not been trained for. Addressing this challenge is a key to fulfilling one of the most appealing promises of machine learning for computational electromagnetics: the rapid solution of problems of interest just by processing the geometry and the sources involved. The impact of such models that can "generalize" to new geometries is more profound for large-scale computations, such as those encountered in wireless propagation scenarios. We present generalizable models for indoor propagation that can predict received signal strengths within new geometries, beyond those of the training set of the model, for transmitters and receivers of multiple positions, and for new frequencies. We show that a convolutional neural network can "learn" the physics of indoor radiowave propagation from ray-tracing solutions of a small set of training geometries, so that it can eventually deal with substantially different geometries. We emphasize the role of exploiting physical insights in the training of the network, by defining input parameters and cost functions that assist the network to efficiently learn basic and complex propagation mechanisms.

Towards Physics-Based Generalizable Convolutional Neural Network Models for Indoor Propagation

A fundamental challenge for machine learning models for electromagnetics is their ability to predict output quantities of interest (such as fields and scattering parameters) in geometries that the model has not been trained for. Addressing this challenge is a key to fulfilling one of the most appealing promises of machine learning for computational electromagnetics: the rapid solution of problems of interest just by processing the geometry and the sources involved. The impact of such models that can "generalize" to new geometries is more profound for large-scale computations, such as those encountered in wireless propagation scenarios. We present generalizable models for indoor propagation that can predict received signal strengths within new geometries, beyond those of the training set of the model, for transmitters and receivers of multiple positions, and for new frequencies. We show that a convolutional neural network can "learn" the physics of indoor radiowave propagation from ray-tracing solutions of a small set of training geometries, so that it can eventually deal with substantially different geometries. We emphasize the role of exploiting physical insights in the training of the network, by defining input parameters and cost functions that assist the network to efficiently learn basic and complex propagation mechanisms.

A SYNTHESIS OF TEMPORAL VARIATIONS IN DOPPLER SPECTRA RECORDED AT A QUASI-VERTICAL INCIDENCE BY THE HF DOPPLER RADAR WITH SPACED RECEIVERS

Purpose: The ionospheric channel is widely used for the communication, radio navigation, radar, direction finding, radio astronomy, and remote radio probing systems. The radio channel parameters are characterized by nonstationarity due to the dynamic processes in the ionosphere, and therefore their study is one of the topical problems of space radio physics and earth-space radio physics of geospace. This work aims at presenting the results of synthesis of temporal variations in the Doppler spectra obtained by the Doppler probing of the ionosphere at vertical and quasi-vertical incidence. Design/methotology/approach: One of the most effective methods of ionosphere research is the Doppler sounding technique. It has a high time resolution (about 10 s), a Doppler shift resolution (0.01–0.1 Hz), and the accuracy of Doppler shift measurements (~0.01 Hz) that permits monitoring the variations in the ionospheric electron density (10–4–10–3) or the study of the ionospheric plasma motion with the speed of 0.1-1 m/s and greater. The solution of the inverse radio physical problem, consisting in determination of the ionosphere parameters, often means solving the direct radio physical problem. In the Doppler sounding technique, it belongs with the construction of variations in Doppler spectra and comparing them with the Doppler spectra measurements. Findings: For the radio wave ordinary component, three echoes being produced by three rays are observed. Influence of the geomagnetic fi eld and large horizontal gradients in the electron density of δ≥10 % give rise to complex ray structures with caustic surfaces. The ionospheric disturbances traveling along the magnetic meridian form the skip zones. The longitudinal and transverse displacement of the ray reflection point attains a few tens of kilometers along the vil. Haidary to vil. Hrakove quasi-vertical radiowave propagation path, for which the great circle range is 50 km. For the vertical incidence, the signal azimuth at the receiver coincides with the traveling ionospheric disturbance azimuth. The synthesis of temporal variations in the HF Doppler spectra has been made and compared with the temporal variations in the Doppler spectra recorded with the V. N. Karazin Kharkiv National University radar. The estimate of δ=15 % obtained confirms the existence of large horizontal gradients in electron density. Conclusions: Temporal variations in Doppler spectra and in azimuth have been calculated for the vertical and quasi-vertical incidence with allowance for large horizontal gradients of the electron density caused by traveling ionospheric disturbances. Key words: ionosphere, Doppler sounding at oblique incidence, synthesis of temporal variations in HF Doppler spectra, traveling ionospheric disturbances, electron density

Adjusting CCIR Maps to Improve Local Behaviour of Ionospheric Models

The objective of this article is to present a concept for single-frequency Global Navigation Satellite System (GNSS) positioning local ionospheric mitigation over a certain area. This concept is based on input parameters driving the NeQuick-G algorithm (the ionospheric single-frequency GNSS correction algorithm adopted by Galileo GNSS system), estimated on a local as opposed to a global scale, from ionospheric characteristics measured by a digital ionosonde and a collocated dual-frequency Total Electron Content (TEC) monitor. This approach facilitates the local adjustment of Committee Consultative for Ionospheric Radiowave propagation (CCIR) files and the Az ionization level, which control the ionospheric electron density profile in NeQuick-G, therefore enabling better estimation of positioning errors under quiet geomagnetic conditions. This novel concept for local ionospheric positioning error mitigation may be adopted at any location where ionospheric characteristics foF2 and M(3000)F2 can be measured, as a means to enhance the accuracy of single-frequency positioning applications based on the NeQuick-G algorithm.

A comparison of catalogues of Forbush decreases identified from individual and a network of neutron monitors: a critical perspective

ABSTRACT Short-term rapid depressions in Galactic cosmic ray (GCR) flux, historically referred to as Forbush decreases (FDs), have long been recognized as important events in the observation of cosmic ray (CR) activity. Although theories and empirical results on the causes, characteristics, and varieties of FDs have been well established, detection of FDs, from either isolated detectors' or arrays of neutron monitor data, remains a subject of interest. Efforts to create large catalogues of FDs began in the 1990s and have continued to the present. In an attempt to test some of the proposed CR theories, several analyses have been conducted based on the available lists. Nevertheless, the results obtained depend on the FD catalogues used. This suggests a need for an examination of consistency between FD catalogues. This is the aim of the present study. Some existing lists of FDs, as well as FD catalogues developed in the current work, were compared, with an emphasis on the FD catalogues selected by the global survey method (GSM). The Forbush effects and interplanetary disturbances database (FEID), created by the Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radiowave Propagation Russian Academy of Sciences (IZMIRAN), is the only available comprehensive and up to date FD catalogue. While there are significant disparities between the IZMIRAN FD and other event lists, there is a beautiful agreement between FDs identified in the current work and those in the FEID. This may be a pointer to the efficiency of the GSM and the automated approach to FD event detection presented here.