Received Signal Level Measurements Research Articles

In-City Rain Mapping from Commercial Microwave Links—Challenges and Opportunities

Obtaining accurate rainfall measurements is highly important in urban areas, having a significant impact on different aspects in city life. Opportunistic rainfall sensing utilizing measurements collected by existing microwave and mmWave-based wireless networks has been researched in the last two decades and can be considered as an opportunistic integrated sensing and communication (ISAC) approach. In this paper, we compare two methods that utilize received signal level (RSL) measurements obtained by an existing smart-city wireless network deployed in the city of Rehovot, Israel, for rain estimation. The first method is a model-based approach using the RSL measurements from short links, in which two design parameters are calibrated empirically. This method is combined with a known wet/dry classification method, which is based on the rolling standard deviation of the RSL. The second method is a data-driven approach, based on a recurrent neural network (RNN), which is trained to estimate rainfall and classify wet/dry periods. We compare the results of rainfall classification and estimation from both methods and show that the data-driven approach slightly outperforms the empirical model and that the improvement is most significant for light rainfall events. Furthermore, we apply both methods to construct high-resolution 2D maps of accumulated rainfall in the city of Rehovot. The ground-level rainfall maps constructed over the city area are compared for the first time with weather radar rainfall maps obtained from the Israeli Meteorological Service (IMS). The rain maps generated by the smart-city network are found to be in agreement with the average rainfall depth obtained from the radar, demonstrating the potential of using existing smart-city networks as a source for constructing 2D high-resolution rainfall maps.

Machine-Learning and 3D Point-Cloud Based Signal Power Path Loss Model for the Deployment of Wireless Communication Systems

Modeling signal power path loss (SPPL) for deployment of wireless communication systems (WCSs) is one of the most time consuming and expensive processes that require data collections during link budget analysis. Radio frequency (RF) engineers mainly employ either deterministic or stochastic approaches for the estimation of SPPL. In the case of stochastic approach, empirical propagation models use predefined estimation parameters for different environments such as reference distance path loss PL(d 0 )(dB), path loss exponent (n), and log-normal shadowing (Xσ with N(σ, μ = 0)). Since empirical models broadly classify the environment under urban, suburban, and rural area, they do not take into account every micro-variation on the terrain. Therefore, empirical models deviate significantly from actual measurements. This paper proposes a smart deployment method of WCS to minimize the need for predefined estimation parameters by creating a 3-D deployment environment which takes into account the micro-variations in the environment. Tree canopies are highly complex structures which create micro-variations and related unidentified path loss due to scattering and absorption. Thus, our proposed model will mainly focus on the effect of tree canopies and can be applied to any environment. The proposed model uses a 2-D image color classification to extract features from a 3-D point cloud and a machine learning (ML) algorithm to predict SPPL. Empirical path loss models have received signal level (RSL) errors in the range of 6.29%-16.9% from the actual RSL measurements while the proposed model has an RSL error of 4.26%.

The Wet-Antenna Effect—A Factor to be Considered in Future Communication Networks

An accurate design of the fading margin in wireless communication networks requires good modeling of the relationship between the rain rate and the attenuation. In this paper, we discuss the effect of the wet antenna (WA) on the fading margin. We claim that this effect is not negligible in commercial $E$ -band (i.e., 60–90 GHz) technologies, where the microwave links are relatively short and the sensitivity of the signal to attenuation induced by rain is significant. Consequently, we propose a method for estimating the WA-induced attenuation, so it can be incorporated in the current models. Different from previous studies, our proposed method can be implemented on received signal level measurements, which are standardly produced by commercial microwave links (CMLs) and a single rain gauge. We demonstrate our results using actual measurements taken by 73 GHz CMLs of about 1 km, provided by Ericsson.

Improved ITU‐R model for digital terrestrial television propagation path loss prediction

The use of a suitable propagation model for coverage prediction is key during the planning and dimensioning process of a digital terrestrial television (DTT) system. This study optimises one of the most detailed models for this purpose, i.e. Recommendation ITU-R.P.1812-4, with the aim of improving its accuracy in propagation path loss prediction for DTT systems in outdoor environments of Caracas city, Venezuela. For model adjustment, it is used the bioinspired technique particle swarm optimisation (PSO) and received signal level measurements performed in DTT systems in Caracas city under fixed reception conditions. The results, quantitatively analysed by RMS error and grey relation grade and mean absolute percentage error, shows a significant increase of the accuracy of optimised model in comparison with the original version and even with others propagation models.

Spatial Sampling Requirements for Received Signal Level Measurements in Cellular Networks of Suburban Area

Spatial Sampling Requirements for Received Signal Level Measurements in Cellular Networks of Suburban Area

The Potential of Microwave Communication Networks to Detect Dew—Experimental Study

At microwave frequencies of tens of GHz, various hydrometeors cause attenuations to the electromagnetic signals. Here, we focus on the effect of liquid water films accumulating on the outer coverage of the microwave units during times of high relative humidity (RH). We propose a novel technique to detect moist antenna losses using standard received signal level (RSL) measurements acquired simultaneously by multiple commercial microwave links (MLs). We use the generalized likelihood ratio test (GLRT) for detecting a transient signal of unknown arrival time and duration. The detection procedure is applied on real RSL measurements taken from an already existing microwave network. It is shown that moist antenna episodes can be detected, information which provides the potential to identify dew, an important hydro-ecological parameter.

Further Validation of an Electromagnetic Macro Model for Analysis of Propagation Path Loss in Cellular Networks Using Measured Driving-Test Data

Received signal level measurements are frequently used to check the performance and the quality of service (QOS) inside the coverage area in cellular networks. These expensive, time-consuming measurements are carried out using actual driving tests to assess the coverage area of a base station for a given cell, and to thus evaluate the quality of service. In a driving-test measurement system, a receiving antenna is placed on top of a vehicle. The vehicle is then driven along radial and circular lines around the base station, to measure the received power and thus assess the quality of service. These driving-test measurements are also used to tune the empirical models in the radio-planning tools that have to be employed for various types of environments. This model tuning is a lengthy procedure. In this paper, it is shown that an electromagnetic macro modeling of the environment can provide simulation results comparable to the data one would obtain in an actual driving-test measurement for a cellular environment. The input parameters for the electromagnetic macro model can be generated using only the physical parameters of the environment, such as the height of the transmitting and receiving antennas over the ground, their tilts towards the ground, and the electrical parameters of the ground. Such analysis can provide realistic plots for the received power as functions of the separation distance between the receiving and the transmitting base-station antennas. The novelty of the electromagnetic-analysis technique proposed in this paper lies in its ability to match the macro-model-based simulation results and the driving-test measurements without any statistical or empirical curve fitting or an ad hoc choice of a reference distance. In addition, a new concept, called the proper route, is introduced to enhance the analysis of the measured data. A Method-of-Moments-based integral-equation-solver code has been used to simulate the effects of the macro parameters of the environment on the propagation-path loss of the signals emanating from a base-station antenna. The perfect match between the simulation results and the driving-test data was illustrated by monitoring the signal levels from some cellular base stations in western India and Sri Lanka, and then comparing the observed results with the simulated results. The goal here is to illustrate that these numerical simulation tools can accurately predict the propagation path loss in a cellular environment without tweaking some non-physical models based on statistical modeling or heuristic assumptions.

Received Signal Level Measurements on a 160 km Line-of-Sight Radio Link

This paper discusses measurement of signals received over a 160-km (100-mi) line-of-sight microwave radio link operating at 8.4 GHz. Signals were recorded at both ends of the path at various times over a period of about 18 months. The effects of macroscale meteorological conditions are mentioned, particularly those which are peculiar to the central European location of the path. The data obtained from this measurement effort are presented both in terms of radio link availability, which includes the effects of diversity improvement, and in terms of long-term propagation performance, which considers only single receiver signal level variability. The data were also analyzed to obtain distributions of fade duration for single receivers and for both receivers in a diversity configuration. The study supports the idea that it is possible to achieve reliable propagation at 8 GHz on a link as long as 160 km, and with less than normal or conventional vertical diversity spacing.