On-site Energy Utilization Evaluation of Telecommunication Base Station: A Case Study of Western Uganda

Due to the widespread installation of Base Stations, the power consumption of cellular communication is increasing rapidly (BSs). Power consumption rises as traffic does, however, this scenario varies from geolocation to geolocation because sites in rural and urban areas have variable traffic loads. Therefore, in order to address various power consumption issues, it is necessary to analyze these sites and offer valid data that network operators can employ. This study took into account the impact of traffic load on energy consumption both in rural and urban locations in western Uganda because prior models did not adequately account for the impact of traffic load on both rural and urban sites. Regression models are used to examine these effects of traffic load on power consumption. Based on measurements taken for twenty-eight days in a row in six urban and rural areas, linear models have been presented. The findings showed that both rural and urban BTS were well-fitted by the suggested linear models. Depending on the layouts of the sites, it was found that energy consumption varied along with traffic, with the number of transceivers present having an impact on both the traffic load and energy consumption

Statistical LOS/NLOS Classification for UWB Channels

Ultrawideband (UWB) technology has attracted a lot of attention for indoor and outdoor positioning systems due to its high accuracy and robustness in non-line-of-sight (NLOS) environments. However, UWB signals are affected by multipath propagation which causes errors in localization. To overcome this problem, researchers have proposed various techniques for NLOS identification and mitigation. One of the approaches is statistical LOS/NLOS classification, which uses statistical parameters of the received signal to distinguish between LOS and NLOS channels. In this paper, we formulated several techniques which can be used for effectively classifying a Line of Sight (LOS) channel from a Non-Line of Sight (NLOS) channel. Various parameters obtained from Channel Impulse Response (CIR) like Skewness, Kurtosis, Root Mean Squared Delay Spread (RDS), Mean Excess Delay (MED), Energy, Energy Ratio, and Mean of Covariance Matrix are used for channel classification. In addition to this, the Joint Probability Density Functions (PDFs) of various parameters are used to improve the accuracy of UWB LOS/NLOS channel classification. Two different criteria-Likelihood Ratio and Hypothesis Tests are used for the identification of the channel

Sensing Technologies for Oxygen Therapy Monitoring: A Survey

Supplemental oxygen is recognized worldwide as a life-saving treatment for first aid, acute and chronic diseases, and this has recently become more important than ever, due to the recent Covid-19 pandemic. This study aims to analyze two important issues related to oxygen therapy in patients with respiratory difficulties, namely oxygen quality and patient safety monitoring. The specific case in which the supply of oxygen fails due to the disconnection of the nasal cannula has no solution in the open literature. As a result, tangible results on how such risk can be avoided are still missing, and hardly any guideline can be found on how to treat this issue from the engineering perspective. In this respect, this work is dedicated to exploring sensing technologies used to detect vital signs and track the patient's condition in real time during therapy, with the aim of defining a starting picture of the current state of the art. The results obtained following the verification of some of the most used sensors in the market are therefore presented and discussed. The integration of these components in an embedded system has also allowed us to understand the practical limits and strengths in terms of complexity and effectiveness of each technology