GraphHO: A Graph-based Handover Optimization System for Cellular Networks
2022 International Symposium on Wireless Communication Systems (ISWCS)(2022)
摘要
Handover optimization is an important task for the load balancing and mobility robustness in cellular networks. However, the cells in a cellular network often overlap and present strong interactions with nearby neighborhood. This renders the handover optimization a challenging problem. In this paper, we propose a novel graph convolutional neural network to capture the complex interaction between overlapping cells. With this graph model, we further develop a contextual bandit solution to optimize the handover efficiency of a cellular networks. Practical challenges derived from the real-world deployment, such as noisy environment and safety constraint, are also well-investigated and addressed. Extensive experiments in a simulation platform and a real-world cellular network demonstrate that our solution can significantly improve the network quality without a prejudice of network stability.
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关键词
Handover optimization,graph convolutional neural networks,contextual bandit
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