2020/10/25 by Srikanth Chandar, Chandar, Srikanth, Muvazima Mansoor +9
Computer Science · Engineering · Social Sciences · #Advanced MIMO Systems Optimization #Applications (stat.AP) #FOS: Computer and information sciences #Human Mobility and Location-Based Analysis #Machine Learning (cs.LG) #Networking and Internet Architecture (cs.NI) #Wireless Communication Networks Research
paper · pdf · doi:10.48550/arxiv.2010.13190
openalex publication_date 2020/10/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With the advent of 4G, there has been a huge consumption of data and the availability of mobile networks has become paramount. Also, with the burst of network traffic based on user consumption, data availability and network anomalies have increased substantially. In this paper, we introduce a novel approach, to identify the regions that have poor network connectivity thereby providing feedback to both the service providers to improve the coverage as well as to the customers to choose the network judiciously. In addition to this, the solution enables customers to navigate to a better mobile network coverage area with stronger signal strength location using Machine Learning Clustering Algorithms, whilst deploying it as a Mobile Application. It also provides a dynamic visual representation of varying network strength and range across nearby geographical areas.