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المؤلفManalastas, Marvin
المؤلفFarooq, Muhammad Umar Bin
المؤلفZaidi, Syed Muhammad Asad
المؤلفAbu-Dayya, Adnan
المؤلفImran, Ali
تاريخ الإتاحة2024-10-20T10:43:19Z
تاريخ النشر2022
اسم المنشورIEEE Transactions on Vehicular Technology
المصدرScopus
الرقم المعياري الدولي للكتاب189545
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/TVT.2022.3157802
معرّف المصادر الموحدhttp://hdl.handle.net/10576/60219
الملخصWith 5G already deployed, challenges related to handover exacerbate due to the dense base station deployment operating on a motley of frequencies. In this paper, we present and evaluate a novel data-driven solution, to reduce inter-frequency handover failures (HOFs), hereafter referred to as TORIS (Transmit Power Tuning-based Handover Success Rate Improvement Scheme). TORIS is designed by developing and integrating two sub-solutions. First sub-solution consists of an Artificial Intelligence (AI)-based model to predict inter-frequency HOFs. In this model, we achieve higher than the state-of-the-art accuracy by leveraging two approaches. First, we devise a novel feature set by exploiting domain knowledge gathered from extensive drive test data analysis. Second, we exploit an extensive set of data augmentation techniques to address the class imbalance in training the HOF prediction model. The data augmentation techniques include Chow-Liu Bayesian Network and Generative Adversarial Network further improved by focusing the sampling only on the borderline. We also compare the performance of state-of-the-art AI models for predicting HOFs with and without augmented data. Results show that AdaBoost yields best performance for predicting HOFs. The second sub-solution is a heuristic scheme to tune the transmit (Tx) power of serving and target cells. Unlike the state-of-the-art approaches for HOF reduction that tune cell individual offset, TORIS targets the main cause of HOFs i.e., poor signal quality and propagation condition, by proactively varying the Tx power of the cells whenever a HOF is anticipated. Results show that TORIS outperforms the state-of-the-art HOF reduction solution and yields 40%-75% reduction in HOFs.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعhandover failure mitigation
Handover failure prediction
handover success rate improvement
inter-frequency handover
العنوانA Data-Driven Framework for Inter-Frequency Handover Failure Prediction and Mitigation
النوعArticle
الصفحات6158-6172
رقم العدد6
رقم المجلد71
dc.accessType Full Text


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