A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Study of Security Mechanisms to Create a Secure Cloud in a Virtual Environment with the Support of Cloud Service Providers
Volume-2 | Issue-3
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
Fault Diagnosis in Hybrid Renewable Energy Sources with Machine Learning Approach
Volume-3 | Issue-3
Secure and Optimized Cloud-Based Cyber-Physical Systems with Memory-Aware Scheduling Scheme
Volume-2 | Issue-3
Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks
Volume-3 | Issue-3
Computer Vision on IOT Based Patient Preference Management System
Volume-2 | Issue-2
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Speedy Detection Module for Abandoned Belongings in Airport Using Improved Image Processing Technique
Volume-3 | Issue-4
Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security
Volume-4 | Issue-3
Design an Early Detection and Classification for Diabetic Retinopathy by Deep Feature Extraction based Convolution Neural Network
Volume-3 | Issue-2
Design of an Intelligent Approach on Capsule Networks to Detect Forged Images
Volume-3 | Issue-3
Future Challenges of the Internet of Things in the Health Care Domain - An Overview
Volume-3 | Issue-4
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
Volume - 2 | Issue - 4 | december 2020
Published
05 January, 2021
The cell selection mechanism that provides services to each mobile station is referred to as cell selection. For maximizing the current and future of cellular networks, it is necessary to optimize the process. The OFDMA-based systems are LTE-Advanced and IEEE 802.16m for satisfying the mobile station minimum demand by having one or more base station simultaneously. The problem is considered as the optimization problem and defines the problem as it is not considered as NP-hard and also not possible for approximation with a reasonable factor. The assumption is that the maximum required bandwidth of a single mobile station is defined as the r-fraction of the capacity of the base station. For cell selection, this paper consists of two algorithms. The first algorithm defines the creation of a (1-r) approximate solution, this is applicable when the coverage of the mobile station is done by one or more base station simultaneously. The second algorithm defines the creation of an approximate solution (1-r /2-r) when the coverage of each mobile station is covered by a maximum one base station. A simulation research that describes the benefit of using our algorithms that have limited and high-loaded power for the future of 4G networks completes the overall study. The performance and capacity are better than the existing algorithms.
KeywordsCellular Networks Cell Selection LTE-Advanced 4G Networks Cell Searching
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