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Channel gain prediction in wireless networks based on spatial-temporal correlation

: Liao, Q.; Valentin, S.; Stańczak, S.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2015 : Stockholm, Sweden, 28 June - 1 July 2015
Piscataway, NJ: IEEE, 2015
ISBN: 978-1-4799-1932-1
ISBN: 978-1-4799-1931-4
International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) <16, 2015, Stockholm>
Conference Paper
Fraunhofer HHI ()

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.