Current Issue : April-June Volume : 2024 Issue Number : 2 Articles : 5 Articles
In this research paper, we introduce a federated learning communication protocol tailored for emergency management applications. Our primary objective is to tackle the communication challenges that arise in such critical scenarios. In order to overcome the limitations associated with centralized server architectures, we present an innovative communication protocol. This protocol empowers the framework to effectively cooperate with multiple centralized servers, fostering efficient knowledge sharing and model training while ensuring the utmost data privacy and security. By harnessing this protocol, our framework elevates the performance and resilience of vital infrastructure systems operating on the Android platform, thereby facilitating real-time operational scenarios. This research makes a substantial contribution to the field of emergency management applications, as we offer a comprehensive solution that optimizes communication and enables seamless collaboration with numerous centralized servers....
This article presents the development of a prototype software for a terrestrial digital TV signal spectrum analyzer using software-defined radio (SDR). This study involves four phases: signal reception from Quito’s TV channels, configuring the software and hardware to work within the 470–698 MHz frequency range using the One-seg service of the ISDB-Tb standard, setting up the spectrum analyzer with a low-pass filter to reduce noise, and analyzing the results by visualizing digital TV signals from various areas of Quito with the SMPlayer software. While capturing TDT signals in Ecuador, it was discovered that some channels’ signals lacked playable audiovisual content on video players during testing....
Recently, fifth-generation (5G) mobile connectivity has been launched in Bangladesh on a trial-run basis. 5G is a super-speed mobile network that is much faster than the existing fourth-generation (4G) technology. It is excruciatingly hard to deploy a fully functioning 5G in any country regardless of its available resources and technological advancements because of some apparent technological complexity and limitations. In addition, when deploying this technology in developing countries such as Bangladesh, the costs come into play. To cope with the world’s advancement in science and technology, Bangladesh is planning to implement 5G covering the whole country. In this paper, we present the major challenges in implementing a wide area 5G network in Bangladesh and find some possible solutions. This research work has also tried to get a clear picture of the service quality of the existing 4G cellular communication by analyzing some of the mobile operators’ download speeds over 24 hours. In addition, this paper presents the current comparison of Internet facilities in Bangladesh with those of other countries across the globe. To the best of our knowledge, there is no publicly available study that has focused on the deployment of the 5G network in Bangladesh after assessing the current state of the cellular network. Therefore, this study could serve as a guiding resource, providing valuable information for decision-making....
Churn is a serious challenge for the telecommunications industry because of the much higher costs of gaining new customers than maintaining existing ones. Therefore, efforts to increase loyalty and decrease customer churn are the focus of telecom’s retention departments. In order to direct antichurn activities, profitable clients who have the highest probability of churning need to be identified. The data used to identify churners are often inaccurate and vague. In this paper, a fuzzy approach to modeling churn intent based on usage data in mobile telecommunications is presented. It appreciates the uncertainty of the data and provides insights into churn modeling. The goal of the study was to evaluate the applicability of the Mamdani and Sugeno models for building a churn model based on a limited but real-world dataset enriched with feature engineering. The additional goal was to find features most usable for churn modeling. Four metrics—accuracy, recall, precision, and F1-score—were used to estimate the performance of the models. The developed fuzzy rule-based systems show that to generalize possible churn identification factors with fuzzy rules, it is advisable to begin with features such as the change in the total amount of the invoice in the last period before the churning compared to the previous one, the total amount of the invoice in the period preceding the churning, the total amount of subscription in two months before the churning, the time of cooperation with the operator, and the number of calls out of the last quarter before leaving....
Deep learning is used in various applications due to its advantages over traditional Machine Learning (ML) approaches in tasks encompassing complex pattern learning, automatic feature extraction, scalability, adaptability, and performance in general. This paper proposes an end-to-end (E2E) delay estimation method for 5G networks through deep learning (DL) techniques based on Gaussian Mixture Models (GMM). In the first step, the components of a GMM are estimated through the Expectation-Maximization (EM) algorithm and are subsequently used as labeled data in a supervised deep learning stage. A multi-layer neural network model is trained using the labeled data and assuming different numbers of E2E delay observations for each training sample. The accuracy and computation time of the proposed deep learning estimator based on the Gaussian Mixture Model (DLEGMM) are evaluated for different 5G network scenarios. The simulation results show that the DLEGMM outperforms the GMM method based on the EM algorithm, in terms of the accuracy of the E2E delay estimates, although requiring a higher computation time. The estimation method is characterized for different 5G scenarios, and when compared to GMM, DLEGMM reduces the mean squared error (MSE) obtained with GMM between 1.7 to 2.6 times....
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