{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/lte-cell-traffic-grow-and-congestion","title":"LTE Cell Traffic Grow and Congestion Forecasting","arxiv_id":null,"date":"2019-04-01","proceeding":"2019 Open Conference of Electrical, Electronic and Information Sciences 2019 4","authors":["Chmieliauskas","D.","Gursnys","D"],"abstract":"Recent popularity grow of predictive analysis is growing in many fields. Importance to forecast mobile traffic for each LTE cell can bring mobile network planning advantages for the operator. It can help operators to spend minimum investing for new sites and cells but be able to guarantee excellent service experience for mobile broadband users. In this paper study of mobile traffic forecasting feasibility using fbProphet algorithm developed by Facebook is presented. Target is to have short term forecasting from which the operator can proactively consider network expansion if the load is too high to satisfy user throughput demands. Five months of daily traffic data used to train model and one month used for forecasting and model testing. Also, 30 days of hourly data were used for busy hour traffic forecasting. In the last part relation between data traffic carried in the LTE cell to cell load explained.","url_abs":"https://ieeexplore.ieee.org/document/8732145","url_pdf":"https://www.researchgate.net/publication/345446849_LTE_Cell_Traffic_Grow_and_Congestion_Forecasting","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"lte-cell-traffic-grow-and-congestion","repo_url":"https://github.com/rdemarqui/traffic_prediction_and_congestion","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}