Propagation Path Loss Research Articles

To Develop a Model for 4g LTE and Predictable 5G at 3500 Mhz that Would Predict the Path Loss for the Environment in Semi-Urban or Mixture of Urban and Rural Surroundings at Specific Geographical Locations

Abstract: In wireless communication, a planned network is given by the path loss model. Link budgeting, coverage prediction, and system performance optimization are indispensable in developing an accurate, simple, and general path loss model. To predict path loss in a particular environment each type of path loss propagation model is designed, it may be inaccurate in another different environment. In this paper, we are trying to predict a path loss model of Durgapur considering a particular place with a mixture of high-rise buildings, sub-urban, open, and foliage environments. For this proposal, the model area has been divided into twelve sectors taking 30° sectoring of radii 5 km and applying the path loss model for the calculation of path loss. Index Terms: Path loss, Predicted model, Outdoor propagation model consideration, Cell site selection, results, and discussions.

Near Ground Pathloss Propagation Model Using Adaptive Neuro Fuzzy Inference System for Wireless Sensor Network Communication in Forest, Jungle and Open Dirt Road Environments.

In Wireless Sensor Networks which are deployed in remote and isolated tropical areas; such as forest; jungle; and open dirt road environments; wireless communications usually suffer heavily because of the environmental effects on vegetation; terrain; low antenna height; and distance. Therefore; to solve this problem; the Wireless Sensor Network communication links must be designed for their best performance using the suitable electromagnetic wave behavior model in a given environment. This study introduces and analyzes the behavior of the LoRa pathloss propagation model for signals that propagate at near ground or that have low transmitter and receiver antenna heights from the ground (less than 30 cm antenna height). Using RMSE and MAE statistical analysis tools; we validate the developed model results. The developed Fuzzy ANFIS model achieves the lowest RMSE score of 0.88 at 433 MHz and the lowest MAE score of 1.61 at 433 MHz for both open dirt road environments. The Optimized FITU-R Near Ground model achieved the lowest RMSE score of 4.08 at 868 MHz for the forest environment and lowest MAE score of 14.84 at 868 MHz for the open dirt road environment. The Okumura-Hata model achieved the lowest RMSE score of 6.32 at 868 MHz and the lowest MAE score of 26.12 at 868 MHz for both forest environments. Finally; the ITU-R Maximum Attenuation Free Space model achieved the lowest RMSE score of 9.58 at 868 MHz for the forest environment and the lowest MAE score of 38.48 at 868 MHz for the jungle environment. These values indicate that the proposed Fuzzy ANFIS pathloss model has the best performance in near ground propagation for all environments compared to other benchmark models.

Propagation Path Loss Models at 28 GHz Using K-Nearest Neighbor Algorithm

Propagation Path Loss Models at 28 GHz Using K-Nearest Neighbor Algorithm

Log Distance Path Loss Model: Application and Improvement for Sub 5 GHz Rural Fixed Wireless Networks

The study of radio signal propagation path loss (PL) is important for planning, designing and evaluating the performance of radio communication networks. However, the state-of-the-art in PL modelling for fixed wireless networks in rural environments is still ill-equipped for making accurate predictions. This paper explores the application of the log distance PL model to heterogeneous fixed wireless networks in harsh rural propagation conditions. This model is then extended and optimized to improve its accuracy. In particular, the dataset is classified according to many criteria, radio links are split into many intervals according to their distances, antenna heights and elevations are integrated into its formula and long-term extreme seasonal variations are considered. Our study uses a wide set of measurements from the fixed wireless networks of a wireless internet service provider in rural regions of Canada. The proposed modifications improve the accuracy by 7 to 15 dB in terms of the root mean squared error.

Millimetre wave 3-D channel modelling for next generation 5G networks

<abstract><p>Millimetre wave (mm-wave) spectrum (30-300GHz) is a key enabling technology in the advent of 5G. However, an accurate model for the mm-wave channel is yet to be developed as the existing 4G-LTE channel models (frequency below 6 GHz) exhibit different propagation attributes. In this paper, a spatial statistical channel model (SSCM) is considered that estimates the characteristics of the channel in the 28, 60, and 73 GHz bands. The SSCM is used to mathematically approximate the propagation path loss in different environments, namely, Urban-Macro, Urban-Micro, and Rural-Macro, under Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions. The New York University (NYU) channel simulator is utilised to evaluate the channel model under various conditions including atmospheric effects, distance, and frequency. Moreover, a MIMO system has been evaluated under mm-wave propagation. The main results show that the 60 GHz band has the highest attenuation compared to the 28 and 73 GHz bands. The results also show that increasing the number of antennas is proportional to the condition number and the rank of the MIMO channel matrix.</p></abstract>

A Fuzzy-Logic Based Path Loss Model at 3.4 GHz for LTE Networks

Empirical and deterministic models have not proven to be effective in path loss predictions because of the problems of computational complexities, low accuracies, and inability to generalize. To solve these problems relating to path loss predictions, this article presents an optimal path loss propagation model developed at 3.4 GHz with the use of fuzzy logic. We introduced Fuzzy logic to accurately represent all forms of uncertainties in the data spectrum as the signal propagates from the transceiver to the receiver, thereby producing accurate results. Experimental data were collected across Cyprus at 3.4 GHz and compared with three existing path loss models. The fuzzy-logic path loss prediction model was then developed and compared with the experimental data and with each of the theoretical empirical models, the newly developed model predicted signal loss with the greatest accuracy as it gives the lowest root-mean-square error. The newly developed model is very efficient for signal propagation and path loss prediction.

In-vivo Experimental Validation of the Attenuation Path Loss Model for Localization of Wireless Implanted Transmitters at 2.45 GHz

Wireless capsule endoscopy (WCE) is a modern, non-invasive method of gastrointestinal examination that can significantly reduce mortality and morbidity. One of the current challenges in WCE is the precise localization of the capsule. An accurate path loss propagation model can be used to find the exact distance from the surface to the capsule inside the abdominal cavity. Unfortunately, there are no standardized In-to-On-Body channel models describing the signal propagation at ultra-high frequencies that are used in the most commercially available WCE systems. This study addresses the gap by conducting an experimental validation of a new propagation model for WCE applications at 2.45 GHz. The results were confirmed by conducting two separate <i>in-vivo</i> trials on porcine animals under general anesthesia. The performance of the model as well as the corresponding ranging errors were evaluated when it was used as an inverse solution for distance estimation to an ingested transmitter. The main advantage of the model is its theoretical basis, which can help further generalize the findings for similar communication scenarios. The obtained ranging error was smaller than one centimeter, suggesting that it can be used for accurate range-based positioning of implanted transmitters.

Propagation Characteristics and Modeling Simulation of Signals in Wireless Channels

This thesis studies the related performance of the hot-research wireless communication systems based on the fading phenomenon of signals in wireless channels, mainly introduces several typical cases of signal fading in the channel, studies the problem of signal attenuation loss, and carries out the Free space propagation Model, the modeling and simulation of the logarithmic path propagation loss model and its modified logarithmic normal shadow path loss model, and analyze the results of these models. In order to realize the construction of a better wireless communication system, according to the analysis of the results of the fading model of the signal in the channel, this thesis also simulates the Okumura model to predict the field strength of different terrains, and combines the correction of the model by Hata to analyze the propagation of radio waves in the wireless channel.

On the Uniqueness of the Quasi-Moment-Method Solution to the Pathloss Model Calibration Problem

Investigations in this paper focus on establishing the uniqueness properties of the Quasi-Moment-Method (QMM) solution to the problem of calibrating nominal radiowave propagation pathloss prediction models. Nominal (basic) prediction models utilized for the investigations, were first subjected to QMM calibrations with measurements from three different propagation scenarios. Then, the nominal models were recast in forms suitable for Singular Value Decomposition (SVD) calibration before being calibrated with both the SVD and QMM algorithms. The prediction performances of the calibrated models as evaluated in terms of Root Mean Square Prediction Error (RMSE), Mean Prediction Error (MPE), and Grey Relational Grade-Mean Absolute Percentage Error (GRG-MAPE) very clearly indicate that the uniqueness of&nbsp; QMM-calibrations of basic pathloss models is more readily observable, when the basic models are recast in forms specific to SVD calibration. In the representative case of calibration with indoor-to-outdoor measurements, RMSE values were recorded for QMM-calibrated nominal models as 5.2639dB for the ECC33 model, and 5.3218dB for the other nominal models. Corresponding metrics for the alternative (rearranged) nominal models emerged as 5.2663dB for the ECC33 model and 5.2591dB for the other models. A similar general trend featured in the GRG-MAPE metrics, which for both SVD and QMM calibrations of all the alternative models, was recorded as 0.9131, but differed slightly (between 0.9138 and 0.9196) for the QMM calibration of the nominal models. The slight differences between these metrics (due to computational round-off approximations) confirm that when the &nbsp;components of basic models are linearly independent, the QMM solution is unique. Planning for wireless communications network deployment may consequently select any basic model of choice for QMM-calibration, and hence, identify relative contributions to pathloss by the model’s component parts.

Extended Weighted ABG: A Robust Non-Linear ABG-Based Approach for Optimal Combination of ABG Path-Loss Propagation Models

This paper proposes a robust non-linear generalized path-loss propagation model, the Extended Weighted ABG (EWABG), which efficiently allows generating a path-loss propagation model by combining several available path-loss datasets (from measurements campaigns) and other previously proposed state-of-the-art 5G path-loss propagation models. The EWABG model works by integrating individual path-loss models into one single model in the least-squares sense, allowing to extend knowledge from frequencies and distances covered by path-loss datasets or path-loss propagation models. The proposed EWABG model is the first non-linear extension of the common ABG-based approach, which surpasses the non-uniformity problem between the low and high 5G frequencies (as most measurements campaigns have taken place in low frequencies). The EWABG also addresses the problem of removing outlier measurements, a step not included in previous propagation path-loss models. In this case, we have compared the most recent techniques for avoiding outliers, and we have adopted the Theil-Sen method, due to its strong robustness demonstrated in the experiments carried out. In addition, the proposed model specifically considers non-linear attenuation by atmospheric gases, in order to improve its estimations. The good performance of the proposed EWABG model has been tested and compared against recent 5G propagation path-loss models including the ABG and WABG models. The exhaustive experimentation carried out includes the 5G non-line-of-sight environment in different 5G scenarios, UMiSC, UMiOS and UMa. The proposed EWABG obtains the best accuracy, specially in noisy environments with outliers, reporting negligible increment error rates (with respect to the non-outliers situation), lower than 1%, compared to the ABG and WABG.

Weighted Direct Position Determination via the Dimension Reduction Method for Noncircular Signals

This work studies the direct position determination (DPD) of noncircular (NC) signals with multiple arrays. Existing DPD algorithms of NC sources ignore the impact of path propagation loss on the performance of the algorithms. In practice, the signal-to-noise ratios (SNRs) of different observation stations are often different and unstable when the NC signal of the same radiation target strikes different observation locations. Besides, NC features of the target signals are applied not only to extend the virtual array manifold but also to bring high-dimensional search. For the sake of addressing the above problems, this study develops a DPD method of NC sources for multiple arrays combing weighted subspace data fusion (SDF) and dimension reduction (RD) search. First, NC features of the target signals are applied to extend the virtual array manifold. Second, we assign a weight to balance the error and obtain higher location accuracy with better robustness. Then, the RD method is used to eliminate the high computational complexity caused by the NC phase search dimension. Finally, the weighted fusion cost function is constructed by using the eigenvalues of the received signal covariance matrixes. It is verified by simulation that the proposed algorithm can effectively improve the location performance, get better robustness, and distinguish more targets compared with two-step location technology and SDF technology. In addition, without losing the estimation performance, the proposed algorithm can significantly reduce the complexity caused by the NC phase search dimension.

Performance Analysis of ZigBeePRO Network Using the Shortest Path Algorithm for Distributed Renewable Generation

The communication requirement for integrating Distributed Renewable Generation (DRG) into Smart Grid (SG) is not strict, where the reliability and critical demand of data delivery are compromised due to the low-data rate and power of ZigBee. However, the presence of various dielectric constant materials in the DRG can cause transmission impairments of the electromagnetic wave. In this paper, we have analysed the performance of the ZigBeePRO network by applying the shortest path algorithm while delivering energy data from the solar DRG to the SG. The DRG architecture is created by considering a real test-bed of 35 kW solar DRG at Universiti Putra Malaysia (UPM). The numbers of nodes are calculated from specifications of the ZigBeePRO enabled Waspmote embedded board, inverters, and electrical parameters of a Photovoltaic (PV) module. The results of the obtained propagation path loss model indicate that the Transverse Electric (TE) and Transverse Magnetic (TM) polarizations are proportional to the loss of the propagation path at different incident angles (α); however, an exception is observed for the TM polarization at α = 55 o. Due to this polarization effect, the brick-built type cabin at the DRG site is a consequence of a higher propagation path loss than the Iron (III)-made cabin. The other performance parameters, including network throughput, data loss, and ZigBeePRO collision, are also evaluated.

A Brief Review of Path Loss Models for mmWave Channels

It is planned to use millimeter wave (mm-wave) communication in 5th Generation (5G) communication systems, as it allows high bandwidth and accordingly high speed data communication. Path loss is one of the most important factors affecting system performance in mm-wave communication. Therefore, path loss must be taken into account in order to create an efficient and reliable mm-wave communication system and to obtain high data rates. It is very important for 5G systems to accurately determine the propagation characteristics and path loss models of the mm-wave communication channel. Many methods have been proposed in the literature to predict path loss with high accuracy and precision in 5G systems. In this review, it is aimed to provide researchers a clear knowledge about path loss in 5G mm-wave communication systems. Papers published between 2018-2021 which based on machine learning, deep learning, neural networks and propagation measurement approach were presented, and the main results of researches related to main path loss models Close-in (CI), and Alpha, Beta, Gamma (ABG) or Floating Intercept (FI) and papers that discussed 3-D ray tracing method were summarized in clear and precise manner.

Relay-Aided Wireless Sensor Network Discovery Algorithm for Dense Industrial IoT Utilizing ESPAR Antennas

Industrial Internet-of-Things (IIoT) applications require reliable and efficient wireless communication. Assuming dense wireless sensor networks (WSNs) operating in a harsh environment, a concept of a time-division multiple access (TDMA)-based WSN enriched with electronically steerable parasitic array radiator (ESPAR) antennas is proposed and examined in this work. The utilized antenna provides one omnidirectional and 12 directional radiation patterns that can be electronically switched by the sensor node. We introduce a relay discovery algorithm, which selects those sensor nodes with an ESPAR antenna capable to act as relay. The selection of the relay nodes is based on a certain link quality threshold that algorithm uses as input. The outcome is a reduction in the number of layers or hops with a guaranteed Quality of Service (QoS). To emphasize the physical aspect of the wireless propagation, we introduce the measured antenna radiation patterns and consider two different path-loss propagation models representing blockage-free and blockage-prone industrial environments. A number of network simulations were performed and signal-to-noise ratio (SNR) as a link quality measure was examined with respect to the network density and different measured radiation pattern settings. The main outcomes show a tradeoff between SNR per link and the percentage of nodes that can serve as relays. As a result, we propose network design guidelines that take under consideration the QoS range with respect to SNR together with an optimal number of antenna radiation patterns that should be selected as a tradeoff between latency, energy consumption, and reliability in a network.

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

&#x0D; &#x0D; &#x0D; 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.&#x0D; &#x0D; &#x0D;

Effect of Membership Functions and Data Size on the Performance of ANFIS-Based Model for Predicting Path Losses in the VHF and UHF Bands

This paper investigates the effect of number and shape of membership function (MF), and training data size on the performance of ANFIS model for predicting path losses in the VHF and UHF bands in built-up environments. Path loss propagation measurements were conducted in four cities of Nigeria over the cellular and broadcasting frequencies. A total of 17 broadcast transmission and cellular base stations were utilized for this study. From the results obtained, it can be concluded for the broadcasting bands that the generalized bell MF shows better performance with an average RMSE of 3.00 dB across all the routes, followed by gaussian, Pi, trapezoid and triangular MFs in that other with average RMSE values of 3.09 dB, 3.11 dB, 3.16 dB and 3.23 dB respectively. For the cellular systems, Triangular MF outperformed other MFs with the lowest average RMSE. The generalized bell MF was found to be suited for WCDMA band while triangular MF is most suited for GSM band. Furthermore, it can also be concluded that the higher the number of membership functions, the lower the RMSE, whereas, a decrease in the data size leads to a reduction in the RMSE values. The findings of this study would help researchers and network planners to make a more informed decision on choosing appropriate system parameters when modeling ANFIS models for path loss prediction.

Path Loss Measurement Validation Using Naïve Bayes Classification for High-Speed Rail

This work proposes path loss measurement validation for high-speed rail wireless communication using Naïve Bayes Classification Method. Path loss propagation model is a major component in wireless network planning in order to meet expected service level requirements and optimized cell towers distribution. However, path loss in high-speed rail propagates rapidly because of unexpected environmental shifts, high mobility, and unique channel modelling. All these unique characteristics lead to inaccuracies and uncertainties in the path loss measurement. Naïve Bayes Classification with Gaussian Classifier offers a better solution in validating path loss measurement than the conventional method for typical wireless communication, which provides statistical descriptions of site-specific environments. The measurement dataset has been taken as continuous values and it is assumed to be distributed according to normal distribution. The dataset has been collected from a running high-speed train. Data discretization has been used as a pre-processing step of transforming continuous data attribute values into a finite set of intervals consisting of path loss in maximum and minimum speed for accuracy or inaccuracy class. The satisfying result of the best performance has been obtained in Accuracy Value (0.9114), Precision Value (0.9147), Recall Value (0.8772), F1-score (0.8956), and Area Under Curve score (0.83). The results have shown that the Naive Bayes method can potentially replace the conventional method in validating path loss measurement, especially for high-speed rail.

Maritime Broadband Communication: Wireless Channel Measurement and Characteristic Analysis for Offshore Waters

For a long time, the development of maritime communication has been restricted by the low data rate, high-latency and high cost of the current communication systems. The upgrade of new generation mobile communication technologies is attracting more and more attention to conduct a shore-based broadband mobile communication network with high-latency and high reliability to serve the maritime industries. This paper presents a solution by means of building a ship-to-infrastructure (S2I) and a ship-to-ship (S2S) wireless communication networks for an offshore region. We characterize the S2I and S2S channels at 5.9 GHz band based on the channel measurements in realistic environments. The channel characteristics, including power delay profile, delay spread, propagation path loss, are extracted and analyzed. In view of the difference between marine and terrestrial communications, we analyze the influencing factors of the offshore water, including effective reflection, divergence and shadowing from the water surface, and diffraction loss caused by the earth curvature. We also predict the power coverage range and the channel capacity for S2I and S2S wireless communications. Finally, the communication performance is evaluated according to the channel measurement and characterization analysis. The research results can be a reference for the construction of maritime communication networks.

A study and Description of the Femtocells Wireless Communication Networks

In this paper the femtocell base station called as Femtocell Access Point (FAP) was descriped and studied. The femtocell (FAP) is fully user deployed and hence reduces the infrastructure, maintenance and operational cost of the operator while at the same time providing good Quality of Service (QoS) to the end user and high network capacity gains. The surest way to increase the system capacity and data rates can be achieved efficiently in a wireless system by getting the transmitter and receiver closer to each other. In a network with nomadic users, this inevitably involves deploying more infrastructure, typically in the form of microcells, hotspots, distributed antennas, or relays. Femtocells deployed in the macrocell significantly improve the indoor coverage and provide better user experience.&#x0D; In this paper the four indoor propagation path loss models with simulated data for different scenarios at 2 GHz are presented In additions the Simulation were carried out in two different scenarios LOS and NLOS for max 50m femtocell and max 100m macrocell network. The simulation results was implemented using Matlab code software.

Assessment and Development of Path Loss Propagation Model for Ikire Metropolis, Nigeria

The aim of this paper is to assess and develop path loss propagation model for terrestial radio broadcasting station in Ikire, Nigeria. In carrying out the study, the reception quality of Osun State Corporation (OSBC) broadcast signal strength within Ikire metropolis in Irewole Local Government Area of Osun State, Nigeria was assessed using BC1173 Field Strength meter. The data obtained from the signal strength measurements around the metropolis were subsequently analysed and used for the development of an ideal propagation path loss model for the metropolis. The developed path loss model for the metropolis was evaluated and found to outperform the COST-231 Hata model in literature. The comparative performance evaluation result of the developed model and the COST-231 Hata model buttresses the need for developing different path loss models for different radio signals in different locations under different environmental factors. In addition, the finding of the study establishes a standard propagation path loss model that can be used for planning and designing efficient wireless communication link for terrestrial radio broadcasting station in the metropolis and any other environments with similar environmental factors.