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• W1567311658 abstract "Due to the popularity of GPS-enabled Smartphones the location of mobile terminals has become widely available [1]. Aided by such location information, we propose a general model to predict the channel gain of mobile users for multiple time steps in advance. Our model exploits spatial and temporal correlation in a Bayesian framework. The framework is composed of an autoregressive process and, according to our analysis of Rayleigh fading, of a multivariate Gaussian process. Numerical results shows that the proposed algorithm (i) achieves much higher accuracy than autoregression, especially for long-term prediction, and (ii) is substantially more robust than support vector machines against localization errors." @default.
• W1567311658 created "2016-06-24" @default.
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• W1567311658 date "2015-06-01" @default.
• W1567311658 modified "2023-10-03" @default.
• W1567311658 title "Channel gain prediction in wireless networks based on spatial-temporal correlation" @default.
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• W1567311658 doi "https://doi.org/10.1109/spawc.2015.7227068" @default.
• W1567311658 hasPublicationYear "2015" @default.
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