Auto-Tuning for Cellular Scheduling Through Bandit-Learning and Low-Dimensional Clustering

IEEE/ACM Transactions on Networking(2021)

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摘要
We propose an online algorithm for clustering channel-states and learning the associated achievable multiuser rates. Our motivation stems from the complexity of multiuser scheduling. For instance, MU-MIMO scheduling involves the selection of a user subset and associated rate selection each time-slot for varying channel states (the vector of quantized channels matrices for each of the users) — a co...
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关键词
Clustering algorithms,Wireless communication,Optimization,Schedules,Transportation,Physical layer,Mathematical model
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