Atmospheric Influence on the Path Loss at High Frequencies for Deployment of 5G Cellular Communication Networks

Over the past few decades, the development of cellular communication technology has spanned several generations in order to add sophisticated features in the updated versions. Moreover, different high-frequency bands are considered for advanced cellular generations. The presence of updated generations like 4G and 5G is driven by the rising demand for a greater data rate and a better experience for end users. However, because 5G-NR operates at a high frequency and has significant propagation, atmospheric fluctuations like temperature, humidity, and rain rate might result in poorer signal reception, and higher path loss effects unlike the prior generation, which employed frequencies below 6 GHz. This paper makes an attempt to provide a comparative analysis about the influence of different relative atmospheric conditions on 5G cellular communication for various operating frequencies in any urban microcell (UMi) environment maintaining the real outdoor propagation conditions. In addition, the simulation dataset based on environmental factors has been validated by the prediction of path loss using multiple regression techniques. Consequently, this study also aims to address the performance analysis of regression techniques for stable estimations of path loss at high frequencies for different atmospheric conditions for 5G mobile generations due to various possible radio link quality issues and fluctuations in different seasons in South Asia. Furthermore, in comparison to contemporary studies, the Machine Learning models have outperformed in predicting the path loss for the four seasons in South Asian regions.Comment: Accepted for presentation at THE 14th INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT

Weather-aware Wake-up of Sleeping Cyber-Physical IoT Nodes

Cyber-physical IoT nodes located in environments which are resource-constrained and physically hard to access, like the Arctic tundra, must achieve long operational lifetimes from a single battery and report data over data networks. The nodes sleep most of the time, and only wake up to perform mission tasks, including reporting data. However, networks can become unavailable, or have low bandwidth and require many re-transmissions for multiple reasons, including a sparse network infrastructure and adverse weather. The state of the network can be quantified by the Received Signal Strength (RSS). If nodes wake up to report data when the signal strength is low they waste energy, because the reporting of data will require more energy or take more accumulated time. RSS decreases with increasing temperature and precipitation. Therefore, nodes should wake up when the temperature and precipitation are low. We explore four algorithms for picking a single time to wake up per 24-hr day over one year. For each wake-up-time, we compute the change in RSS as a function of the change in temperature and precipitation. We use historic weather forecasts and measurements from MET Norway. The data covers 37 locations in Northern Norway over one year. The weather-forecast-based algorithm is able to frequently select a timeslot near the highest expected RSS. It also avoids the large decrease in RSS caused by precipitation more often than the other algorithms presented

RF Coverage Planning And Analysis With Adaptive Cell Sectorization In Millimeter Wave 5G Networks

The advancement of Fifth Generation Network (5G) technology is well underway, with Mobile Network Operators (MNOs) globally commencing the deployment of 5G networks within the mid-frequency spectrum range (3GHz–6GHz). Nevertheless, the escalating demands for data traffic are compelling MNOs to explore the high-frequency spectrum (24GHz–100GHz), which offers significantly larger bandwidth (400MHz-800 MHz) compared to the mid-frequency spectrum (3GHz–6GHz), which typically provides 50MHz-100MHz of bandwidth. However, it is crucial to note that the higher-frequency spectrum imposes substantial challenges due to exceptionally high free space propagation loss, resulting in 5G cell site coverage being limited to several hundred meters, in contrast to the several kilometers achievable with 4G. Consequently, MNOs are faced with the formidable task of accurately planning and deploying hundreds of new 5G cells to cover the same areas served by a single 4G cell.This dissertation embarks on a comprehensive exploration of Radio Frequency (RF) coverage planning for 5G networks, initially utilizing a conventional three-sector cell architecture. The coverage planning phase reveals potential challenges, including coverage gaps and poor Signal-to-Interference-plus-Noise Ratio (SINR). In response to these issues, the dissertation introduces an innovative cell site architecture that embraces both nine and twelve sector cells, enhancing RF coverage through the adoption of an advanced antenna system designed with subarrays, offering adaptive beamforming and beam steering capabilities. To further enhance energy efficiency, the dissertation introduces adaptive higher-order cell-sectorization (e.g., nine sector cells and twelve sector cells). In this proposed method, all sectors within a twelve-sector cell remain active during peak hours (e.g., daytime) and are reduced to fewer sectors (e.g., nine sectors or six sectors per cell) during off-peak hours (e.g., nighttime). This dynamic adjustment is facilitated by an advanced antenna system utilizing sub-array architecture, which employs adaptive beamforming and beam steering to tailor the beamwidth and radiation angle of each active sector. Simulation results unequivocally demonstrate significant enhancements in RF coverage and SINR with the implementation of higher-order cell-sectorization. Furthermore, the proposed adaptive cell-sectorization method significantly reduces energy consumption during off-peak hours. In addition to addressing RF coverage planning, this dissertation delves into the numerous challenges associated with deploying 5G networks in the higher frequency spectrum (30GHz-300GHz). It encompasses issues such as precise cell site planning, location acquisition, propagation modeling, energy efficiency, backhauling, and more. Furthermore, the dissertation offers valuable insights into future research directions aimed at effectively surmounting these challenges and optimizing the deployment of 5G networks in the high-frequency spectrum

Air Quality Prediction in Smart Cities Using Machine Learning Technologies Based on Sensor Data: A Review

The influence of machine learning technologies is rapidly increasing and penetrating almost in every field, and air pollution prediction is not being excluded from those fields. This paper covers the revision of the studies related to air pollution prediction using machine learning algorithms based on sensor data in the context of smart cities. Using the most popular databases and executing the corresponding filtration, the most relevant papers were selected. After thorough reviewing those papers, the main features were extracted, which served as a base to link and compare them to each other. As a result, we can conclude that: (1) instead of using simple machine learning techniques, currently, the authors apply advanced and sophisticated techniques, (2) China was the leading country in terms of a case study, (3) Particulate matter with diameter equal to 2.5 micrometers was the main prediction target, (4) in 41% of the publications the authors carried out the prediction for the next day, (5) 66% of the studies used data had an hourly rate, (6) 49% of the papers used open data and since 2016 it had a tendency to increase, and (7) for efficient air quality prediction it is important to consider the external factors such as weather conditions, spatial characteristics, and temporal features

Wireless Channel Path-Loss Modelling for Agricultural and Vegetation Environments: A Survey

This work undertakes an extensive survey of the channel modelling methods and path-loss characterization carried out in agricultural fields and vegetation environments in an attempt to study the state-of-the-art in this field, which, though vastly explored, still presents extremely diverse opportunities and challenges. The interface for communication between nodes in a typical agricultural field is the wireless channel or air interface, making it imperative to address the impairments that are exclusive to such a communication scenario by studying the characteristics of the medium. The performance of the channel is a direct indicator of the quality of communication. It is required to have a lucid understanding of the channel to ensure quality in transmission of the required information, while simultaneously ensuring maximum capacity by employing limited resources. The impairments that are the very nature of a typical wireless channel are treated in an explicit manner covering the theoretical and mathematical models, analytical aspects and empirical models. Although there are several propagation models characterized for generic indoor and outdoor environments, these cannot be applied to agricultural, vegetation, forest and foliage scenarios due to the various additional factors that are specific to these environments. Owing to the wide variety, size, properties and span of the foliage, it also becomes extremely challenging to develop a generic predictive model for all kinds of crops or vegetation. The survey is categorized into fields containing specific crops, greenhouse environment and forest/foliage scenarios and the key findings are presented

Investigation of Diurnal Variation of Signal Strength Generated by FM Transmitter

This paper focuses on the determination of the diurnal variation of signal strength generated by Orient 94.4 FM transmitter along six (6) selected route in Imo State, Nigeria. This was carried out with the aid of a constructed signal strength meter (SSM). Signal strength measurements were collected at different time, on different days, and in different months. The measurement was carried out at a constant distance of 20 Km. Arrangement was made with the management of the base station to ensure that the transmitting parameters were kept constant throughout the period of signal strength measurement. The average results of these measurements were taken. The data obtained from the measurements was plotted in a graph to establish the diurnal variation in signal strength along the different routes of signal strength measurement. It was observed from this research that transmission and reception of signals are dependent on the time of the day. High signal strength was noted between the hours of 8 am and 11 am, while low signal strength was recorded between the hours of 1 pm and 5 pm. Better signal strengths were recorded at night. The result of this study shows that signal strength generated by FM transmitter vary with time of the day and the prevalent weather conditions. Stronger signals are recorded mostly at night along the different routes of the study. The signal strength consequently drops in the afternoon and recovers in the morning hours

Asia’s Wicked Environmental Problems

The developing economies of Asia are confronted by serious environmental problems that threaten to undermine future growth, food security, and regional stability. This study considers four major environmental challenges that policymakers across developing Asia will need to address towards 2030: water management, air pollution, deforestation and land degradation, and climate change. We argue that these challenges, each unique in their own way, all exhibit the characteristics of “wicked problems”. As developed in the planning literature, and now applied much more broadly, wicked problems are dynamic, complex, encompass many issues and stakeholders, and evade straightforward, lasting solutions.asia environmental problems; food security; water management; air pollution; deforestation; land degradation; climate change; wicked problems

Proceedings of 2010 Kentucky Water Resources Annual Symposium

This conference was planned and conducted as part of the state water resources research annual program with the support and collaboration of the Department of the Interior, U.S. Geological Survey and the University of Kentucky Research Foundation, under Grant Agreement Number 06HQGR0087. The views and conclusions contained in this document and presented at the symposium are those of the abstract authors and presenters and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Government or other symposium organizers and sponsors