{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T02:35:04Z","timestamp":1773801304202,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,21]],"date-time":"2021-08-21T00:00:00Z","timestamp":1629504000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>Mobile networks management is increasingly critical due to heavy communications usage by customers and complex due to the multiple technologies and systems deployed. Thus, Mobile Network Operators (MNOs) are constantly looking for better software solutions and tools to help them increase network performance and manage their networks more efficiently. In this paper, we present a modular web-based software solution to tackle problems related to mobile network planning, operation and optimization. The solution is focused on a set of functional requirements carefully chosen to support the network life cycle management, from planning to Operation and Maintenance (OAM) and optimisation stages. Based on a 3-tier modular architecture and implemented using only open-source software, the solution handles multiple data sources (e.g., Drive Test (DT) and Performance Management (PM)) and multiple Radio Access Network (RAN) technologies. MNOs can explore all available data through a flexible and user-friendly web interface, that also includes map-based visualization of the network. Moreover, the solution incorporates a set of recently developed and validated RAN algorithms, supporting tasks of network diagnosis, optimization, and planning. Also, with the purpose of optimizing the network, MNOs can investigate network simulations, using the RAN algorithms, of how the network will behave under certain conditions, and visualize the outcome of those simulations.<\/jats:p>","DOI":"10.3390\/app11167686","type":"journal-article","created":{"date-parts":[[2021,8,22]],"date-time":"2021-08-22T21:42:12Z","timestamp":1629668532000},"page":"7686","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Modular Web-Based Software Solution for Mobile Networks Planning, Operation and Optimization"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3685-0659","authenticated-orcid":false,"given":"Adriano","family":"Lopes","sequence":"first","affiliation":[{"name":"Department of Information Science and Technology, Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal"},{"name":"Information Sciences, Technologies and Architecture Research Center (ISTAR-IUL), 1649-026 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4654-0881","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Oliveira","sequence":"additional","affiliation":[{"name":"Department of Information Science and Technology, Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal"},{"name":"Instituto de Telecomunica\u00e7\u00f5es, 1049-001 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7729-4033","authenticated-orcid":false,"given":"Pedro","family":"Sebasti\u00e3o","sequence":"additional","affiliation":[{"name":"Department of Information Science and Technology, Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal"},{"name":"Instituto de Telecomunica\u00e7\u00f5es, 1049-001 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2471-170X","authenticated-orcid":false,"given":"Marco","family":"Sousa","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, 1049-001 Lisboa, Portugal"},{"name":"Departamento de Engenharia Electrot\u00e9cnica e de Computadores, Instituto Superior T\u00e9cnico (IST), 1049-001 Lisboa, Portugal"},{"name":"Celfinet\u2014Outstanding Networks, 1495-764 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0279-8741","authenticated-orcid":false,"given":"Pedro","family":"Vieira","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, 1049-001 Lisboa, Portugal"},{"name":"Departamento de Engenharia Electr\u00f3nica e Telecomunica\u00e7\u00f5es e de Computadores, Instituto Superior de Engenharia de Lisboa (ISEL), 1959-007 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1109\/MCOM.2019.1800374","article-title":"Big Data Analytics for Automated QoE Management in Mobile Networks","volume":"57","author":"Garcia","year":"2019","journal-title":"IEEE Commun. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1109\/COMST.2018.2868922","article-title":"Fault Management in Software-Defined Networking: A Survey","volume":"21","author":"Yu","year":"2019","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1109\/COMST.2017.2773462","article-title":"Toward an Efficient C-RAN Optical Fronthaul for the Future Networks: A Tutorial on Technologies, Requirements, Challenges, and Solutions","volume":"20","author":"Alimi","year":"2018","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1109\/JIOT.2015.2415522","article-title":"Profiling Wireless Resource Usage for Mobile Apps via Crowdsourcing-Based Network Analytics","volume":"2","author":"Ouyang","year":"2015","journal-title":"IEEE Internet Things J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1109\/TBDATA.2017.2734100","article-title":"Assembling and Using a Cellular Dataset for Mobile Network Analysis and Planning","volume":"4","author":"Malandrino","year":"2018","journal-title":"IEEE Trans. Big Data"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1109\/MWC.001.1900323","article-title":"Artificial Intelligence-Enabled Cellular Networks: A Critical Path to Beyond-5G and 6G","volume":"27","author":"Shafin","year":"2020","journal-title":"IEEE Wirel. Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/MCOM.001.1900664","article-title":"When Machine Learning Meets Wireless Cellular Networks: Deployment, Challenges, and Applications","volume":"58","author":"Challita","year":"2020","journal-title":"IEEE Commun. Mag."},{"key":"ref_8","unstructured":"Forsk (2021, February 02). Atoll Radio Planning Software Overview (RF Planning and Optimisation)|Forsk. Available online: https:\/\/www.forsk.com\/atoll-overview."},{"key":"ref_9","unstructured":"TEOCO (2021, February 02). Radio Network Planning\u2014TEOCO. Available online: https:\/\/www.teoco.com\/products-services\/ran-solutions\/planning\/radio-planning\/."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1109\/TST.2014.6733212","article-title":"Mobile Internet big data platform in China Unicom","volume":"19","author":"Huang","year":"2014","journal-title":"Tsinghua Sci. Technol."},{"key":"ref_11","unstructured":"Telecom Engineering Centre of Excellence (TEE) (2020). The Age of Telecom Network Automation: Automating Engineering and Network Operation RAN Processes, TEE. Technical Report."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Xu, L., Shao, G., Cao, Y., Yang, H., Sun, C., Zhang, T., Wen, B., Cheng, X., Song, C., and He, X. (2019, January 21\u201323). Research on Telecom Big Data Platform of LTE\/5G Mobile Networks. Proceedings of the 2019 IEEE International Conferences on Ubiquitous Computing Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS), Shenyang, China.","DOI":"10.1109\/IUCC\/DSCI\/SmartCNS.2019.00155"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kassela, E., Provatas, N., Tsiourvas, A., Konstantinou, I., and Koziris, N. (2019, January 9\u201312). BigOptiBase: Big Data Analytics for Base Station Energy Consumption Optimization. Proceedings of the 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA.","DOI":"10.1109\/BigData47090.2019.9005502"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Rueda, D.F., Vergara, D., and Reniz, D. (2018, January 10\u201313). Big Data Streaming Analytics for QoE Monitoring in Mobile Networks: A Practical Approach. Proceedings of the 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA.","DOI":"10.1109\/BigData.2018.8622590"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Suleykin, A., and Panfilov, P. (2019, January 8\u201312). Distributed Big Data Driven Framework for Cellular Network Monitoring Data. Proceedings of the 24th Conference of Open Innovations Association, FRUCT 2019, Moscow, Russia.","DOI":"10.23919\/FRUCT.2019.8711912"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wen, J., and Li, V.O.K. (2016, January 23\u201326). Big-Data-Enabled Software-Defined Cellular Network Management. Proceedings of the 2016 International Conference on Software Networking (ICSN), Jeju Island, Korea.","DOI":"10.1109\/ICSN.2016.7501923"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"D126","DOI":"10.1364\/JOCN.10.00D126","article-title":"Machine learning for network automation: Overview, architecture, and applications [Invited Tutorial]","volume":"10","author":"Rafique","year":"2018","journal-title":"IEEE\/OSA J. Opt. Commun. Netw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.1109\/JIOT.2016.2624761","article-title":"Deep Network Analyzer (DNA): A Big Data Analytics Platform for Cellular Networks","volume":"4","author":"Yang","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"39807","DOI":"10.1109\/ACCESS.2018.2847609","article-title":"Unsupervised Learning Algorithm for Intelligent Coverage Planning and Performance Optimization of Multitier Heterogeneous Network","volume":"6","author":"Gazda","year":"2018","journal-title":"IEEE Access"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"12043","DOI":"10.1109\/TVT.2020.3011147","article-title":"Network Optimisation in 5G Networks: A Radio Environment Map Approach","volume":"69","author":"Rodriguez","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_21","unstructured":"Duarte, D., Pinto, I., and Vieira, P. (2018, January 25\u201328). An Improved Capacity Model based on Radio Measurements for a 4G and beyond Wireless Network. Proceedings of the 21st International Symposium on Wireless Personal Multimedia Communications, WPMC 2018, Chiang Rai, Thailand."},{"key":"ref_22","first-page":"12","article-title":"Self-Optimization of Low Coverage and High Interference in Real 3G\/4G Radio Access Networks","volume":"3","author":"Sousa","year":"2018","journal-title":"i-ETC ISEL Acad. J. Electron. Telecommun. Comput."},{"key":"ref_23","unstructured":"Duarte, D., Vieira, P., Rodrigues, A.J., and Silva, N.S. (2015, January 13\u201316). A New Approach for Crossed Sector Detection in Live Mobile Networks based on Radio Measurements. Proceedings of the Wireless Personal Multimedia Communications Symp, WPMC, Hyderabad, India."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Jales, G., Sousa, M., and Vieiral, P. (2019, January 24\u201327). Optimizing the 4G Mobility Strategy after Diagnosing Network Sub-Performance Areas. Proceedings of the 2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC), Lisbon, Portugal.","DOI":"10.1109\/WPMC48795.2019.9096061"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Alves, A., Sousa, M., Vieira, P., Queluz, M.P., and Rodrigues, A. (2020, January 19\u201326). A New 3D Beamforming Antenna Model for 5G Propagation Modeling based on Real Data. Proceedings of the 2020 23rd International Symposium on Wireless Personal Multimedia Communications (WPMC), Virtual Edition, Okayama, Japan.","DOI":"10.1109\/WPMC50192.2020.9309503"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Saraiva, T., Duarte, D., Pinto, I., and Vieira, P. (2020, January 17\u201320). An Improved BBU\/RRU Energy Consumption Predictor for 4G and Legacy Mobile Networks using Mixed Statistical Models. Proceedings of the 2020 International Conference on Computing, Networking and Communications (ICNC), Big Island, HI, USA.","DOI":"10.1109\/ICNC47757.2020.9049673"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Northwood, C. (2018). The Full Stack Developer: Your Essential Guide to the Everyday Skills Expected of a Modern Full Stack Web Developer, Apress. [1st ed.].","DOI":"10.1007\/978-1-4842-4152-3"},{"key":"ref_28","unstructured":"Shneiderman, B. (1996, January 3\u20136). The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. Proceedings of the 1996 IEEE Symposium on Visual Languages, Boulder, CO, USA."},{"key":"ref_29","unstructured":"(2021, January 12). GitHub\u2014Facebook\/React: A Declarative, Efficient, and Flexible JavaScript Library for Building User Interfaces. Available online: https:\/\/github.com\/facebook\/react."},{"key":"ref_30","unstructured":"(2021, January 12). Material-UI: A Popular React UI Framework. Available online: https:\/\/material-ui.com\/."},{"key":"ref_31","unstructured":"(2021, January 12). Leaflet\u2014A JavaScript Library for Interactive Maps. Available online: https:\/\/leafletjs.com\/."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2301","DOI":"10.1109\/TVCG.2011.185","article-title":"D3 Data-Driven Documents","volume":"17","author":"Bostock","year":"2011","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_33","unstructured":"(2021, January 12). The Web Framework for Perfectionists with Deadlines | Django. Available online: https:\/\/www.djangoproject.com\/."},{"key":"ref_34","unstructured":"ETSI (2013). LTE; Evolved Universal Terrestrial Radio Access (E-UTRA). Requirements for Support of Radio Resource Management, European Telecommunications Standards Institute. Technical Specification (TS) 36.133. Version 9.16.0."}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/11\/16\/7686\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:48:31Z","timestamp":1760165311000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/11\/16\/7686"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,21]]},"references-count":34,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["app11167686"],"URL":"https:\/\/doi.org\/10.3390\/app11167686","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,21]]}}}