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Partially Observable Markov Decision Process-Based Transmission Policy over Ka-Band Channels for Space Information Networks

Communication Engineering Research Centre, Harbin Institute of Technology Shenzhen, HIT Campus of University Town of Shenzhen, Shenzhen 518055, China
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These authors contributed equally to this work.
Entropy 2017, 19(10), 510; https://doi.org/10.3390/e19100510
Received: 24 July 2017 / Revised: 30 August 2017 / Accepted: 20 September 2017 / Published: 21 September 2017
(This article belongs to the Section Information Theory, Probability and Statistics)
The Ka-band and higher Q/V band channels can provide an appealing capacity for the future deep-space communications and Space Information Networks (SIN), which are viewed as a primary solution to satisfy the increasing demands for high data rate services. However, Ka-band channel is much more sensitive to the weather conditions than the conventional communication channels. Moreover, due to the huge distance and long propagation delay in SINs, the transmitter can only obtain delayed Channel State Information (CSI) from feedback. In this paper, the noise temperature of time-varying rain attenuation at Ka-band channels is modeled to a two-state Gilbert–Elliot channel, to capture the channel capacity that randomly ranging from good to bad state. An optimal transmission scheme based on Partially Observable Markov Decision Processes (POMDP) is proposed, and the key thresholds for selecting the optimal transmission method in the SIN communications are derived. Simulation results show that our proposed scheme can effectively improve the throughput. View Full-Text
Keywords: space information networks; Ka-band; Gilbert–Elliot channel; partially observable Markov decision processes space information networks; Ka-band; Gilbert–Elliot channel; partially observable Markov decision processes
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Jiao, J.; Sui, X.; Gu, S.; Wu, S.; Zhang, Q. Partially Observable Markov Decision Process-Based Transmission Policy over Ka-Band Channels for Space Information Networks. Entropy 2017, 19, 510.

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