Cell state prediction through distributed estimation of transmit power
Asghar, Muhammad Zeeshan; Azhar, Farhan; Nauman, Muhammad; Ali, Nouman; Maqbool, Muaz; Ilyas, Muhammad Saqib; Baig, Mirza Mubasher (2019). Cell state prediction through distributed estimation of transmit power. In Galinina, Olga; Andreev, Sergey; Balandin, Sergey; Koucheryavy, Yevgeni (Eds.) NEW2AN 2019, ruSMART 2019 : Internet of Things, Smart Spaces, and Next Generation Networks and Systems : Proceedings of the 19th International Conference on Next Generation Wired/Wireless Networking, and 12th Conference on Internet of Things and Smart Spaces, Lecture Notes in Computer Science, 11660. Cham: Springer, 365-376. DOI: 10.1007/978-3-030-30859-9_31
Published inLecture Notes in Computer Science
© Springer Nature Switzerland AG 2019
Determining the state of each cell, for instance, cell outages, in a densely deployed cellular network is a difficult problem. Several prior studies have used minimization of drive test (MDT) reports to detect cell outages. In this paper, we propose a two step process. First, using the MDT reports, we estimate the serving base station’s transmit power for each user. Second, we learn summary statistics of estimated transmit power for various networks states and use these to classify the network state on test data. Our approach is able to achieve an accuracy of 96% on an NS-3 simulation dataset. Decision tree, random forest and SVM classifiers were able to achieve a classification accuracy of 72.3%, 76.52% and 77.48%, respectively .
Parent publication ISBN978-3-030-30858-2
ConferenceInternational Conference on Next Generation Wired/Wireless Advanced Networks and Systems
Is part of publicationNEW2AN 2019, ruSMART 2019 : Internet of Things, Smart Spaces, and Next Generation Networks and Systems : Proceedings of the 19th International Conference on Next Generation Wired/Wireless Networking, and 12th Conference on Internet of Things and Smart Spaces
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