scholarly journals Wireless Underground Communications in Sewer and Stormwater Overflow Monitoring: Radio Waves through Soil and Asphalt Medium

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 98 ◽  
Author(s):  
Usman Raza ◽  
Abdul Salam
Keyword(s):  
Path Loss ◽  
Storm Water ◽  
Radio Waves ◽  
Loss Analysis ◽  
Underground Communication ◽  
Loss Prediction ◽  
Underground Infrastructure ◽  
Path Loss Prediction ◽  
Sewer Overflow ◽  
Underground Communications

Storm drains and sanitary sewers are prone to backups and overflows due to extra amount wastewater entering the pipes. To prevent that, it is imperative to efficiently monitor the urban underground infrastructure. The combination of sensors system and wireless underground communication system can be used to realize urban underground IoT applications, e.g., storm water and wastewater overflow monitoring systems. The aim of this article is to establish a feasibility of the use of wireless underground communications techniques, and wave propagation through the subsurface soil and asphalt layers, in an underground pavement system for storm water and sewer overflow monitoring application. In this paper, the path loss analysis of wireless underground communications in urban underground IoT for wastewater monitoring has been presented. The dielectric properties of asphalt, sub-grade aggregates, and soil are considered in the path loss analysis for the path loss prediction in an underground sewer overflow and wastewater monitoring system design. It has been shown that underground transmitter was able to communicate through thick asphalt (10 cm) and soil layers (20 cm) for a long range of up to 4 km.

scholarly journals Testing a 5G Communication System: Kriging-Aided O2I Path Loss Modeling Based on 3.5 GHz Measurement Analysis

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6716
Author(s):  
Melissa Eugenia Diago-Mosquera ◽  
Alejandro Aragón-Zavala ◽  
Mauricio Rodriguez
Keyword(s):  
Path Loss ◽  
Random Variable ◽  
Wireless Channel ◽  
Average Error ◽  
Radio Waves ◽  
Radio Access ◽  
Measurement Analysis ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
Radio Measurements

Deep knowledge of how radio waves behave in a practical wireless channel is required for the effective planning and deployment of radio access networks in outdoor-to-indoor (O2I) environments. Using more than 400 non-line-of-sight (NLOS) radio measurements at 3.5 GHz, this study analyzes and validates a novel O2I measurement-based path loss prediction narrowband model that characterizes and estimates shadowing through Kriging techniques. The prediction results of the developed model are compared with those of the most traditional assumption of slow fading as a random variable: COST231, WINNER+, ITU-R, 3GPP urban microcell O2I models and field measured data. The results showed and guaranteed that the predicted path loss accuracy, expressed in terms of the mean error, standard deviation and root mean square error (RMSE) was significantly better with the proposed model; it considerably decreased the average error for both scenarios under evaluation.

scholarly journals Fusing Diverse Input Modalities for Path Loss Prediction: A Deep Learning Approach

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 30441-30451
Author(s):  
Sotirios P. Sotiroudis ◽  
Panagiotis Sarigiannidis ◽  
Sotirios K. Goudos ◽  
Katherine Siakavara
Keyword(s):  
Deep Learning ◽  
Path Loss ◽  
Learning Approach ◽  
Loss Prediction ◽  
Path Loss Prediction

Calibration of Empirical Models for Path Loss Prediction in Urban Environment

2020 ◽  
pp. 301-310
Author(s):  
Robert O. Abolade ◽  
Dare J. Akintade ◽  
Segun I. Popoola ◽  
Folasade A. Semire ◽  
Aderemi A. Atayero ◽  
...  
Keyword(s):  
Urban Environment ◽  
Path Loss ◽  
Empirical Models ◽  
Loss Prediction ◽  
Path Loss Prediction

scholarly journals Path loss prediction model development in a mountainous forest environment

2021 ◽  
pp. 1-1
Author(s):  
Bilguunmaa Myagmardulam ◽  
Tadachika Nakayama ◽  
Kazuyoshi Takahashi ◽  
Ryu Miura ◽  
Fumie Ono ◽  
...  
Keyword(s):  
Prediction Model ◽  
Model Development ◽  
Path Loss ◽  
Forest Environment ◽  
Loss Prediction ◽  
Path Loss Prediction

scholarly journals Measurement and Prediction of Short-Range Path Loss between 27 and 40 GHz in University Campus Scenarios

2020 ◽  
Author(s):  
Glaucio Ramos ◽  
Carlos Vargas ◽  
Luiz Mello ◽  
Paulo Pereira ◽  
Sandro Gonçalves ◽  
...  
Keyword(s):  
Short Range ◽  
Prediction Models ◽  
Path Loss ◽  
Prediction Method ◽  
University Campus ◽  
Millimetre Wave ◽  
Empirical Prediction ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
Path Loss Measurements

Abstract In this paper, we present the results of short-range path loss measurements in the microwave and millimetre wave bands, at frequencies between 27 and 40 GHz, obtained in a campaign inside a university campus in Rio de Janeiro, Brazil. Existing empirical path loss prediction models, including the alpha-beta-gamma (ABG) model and the close-in free space reference distance with frequency dependent path loss exponent (CIF) model are tested against the measured data, and an improved prediction method that includes the path loss dependence on the height di erence between transmitter and receiver is proposed. A fuzzy technique is also applied to predict the path loss and the results are compared with those obtained with the empirical prediction models.

scholarly journals Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Quadri Ramon Adebowale ◽  
Nasir Faruk ◽  
Kayode S. Adewole ◽  
Abubakar Abdulkarim ◽  
Lukman A. Olawoyin ◽  
...  
Keyword(s):  
Computational Intelligence ◽  
Path Loss ◽  
Channel Modeling ◽  
Radio Propagation ◽  
Future Research ◽  
Computational Techniques ◽  
Research Issues ◽  
Main Research ◽  
Loss Prediction ◽  
Path Loss Prediction

The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over-emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction.

scholarly journals Semi Deterministic Hybrid Model for Path Loss Prediction Improvement

2016 ◽  
Vol 92 ◽  
pp. 336-344 ◽  
Author(s):  
A. Bhuvaneshwari ◽  
R. Hemalatha ◽  
T. Satyasavithri
Keyword(s):  
Hybrid Model ◽  
Path Loss ◽  
Loss Prediction ◽  
Path Loss Prediction
Sign in / Sign up

Export Citation Format

Share Document