NDLI: A modified ARIMA model for CQI prediction in LTE-based mobile satellite communications

Content Provider	IEEE Xplore Digital Library
Author	Yadan Zheng Shubo Ren Xiaoyan Xu Ying Si Mingke Dong Jianjun Wu
Copyright Year	2012
Description	Author affiliation: Institution of Advanced Communications, EECS, Room 2350, Science building 2, Peking University, Beijing, China (Mingke Dong) \|\| Institution of Advanced Communications, EECS, Room 2341, Science building 2, Peking University, Beijing, China (Jianjun Wu) \|\| Institution of Advanced Communications, EECS, Room 2352, Science buding 2, Peking University, Beijing, China (Yadan Zheng) \|\| Institution of Advanced Communications, EECS, Room 2353, Science building 2, Peking University, Beijing, China (Shubo Ren; Xiaoyan Xu; Ying Si)
Abstract	LTE-based mobile satellite communication system is a combination of terrestrial LTE system and satellite communication techniques, which aims at improving the current LTE system's technical specifications for better service quality. AMC (Adaptive Modulation and Coding) technique is applied in current LTE system to improve system capacity and data transmission efficiency. CQI (Channel Quality Indicator), which is measured by UE, is an essential indicator for AMC process. However in satellite system, the said data received by eNodeB are all outdated due to the long delay caused by satellite link. So there exists need for predicting CQI data in advance. ARIMA (Autoregressive Integrated Moving Average Model) is a good choice for predicting CQI in terrestrial system, but its prediction ability is limited when prediction length is too long in satellite communication system. To solve this problem, a prediction scheme is proposed in this paper. This method predicts CQI states, instead of predicting the specific CQI values, and provides the reference CQI for AMC. A modified ARIMA model is applied for reducing the prediction complexity and delay. Simulation shows that the proposed method can realize CQI prediction with acceptable RMSE performance.
Starting Page	822
Ending Page	826
File Size	740287
Page Count	5
File Format	PDF
ISBN	9781457703430
e-ISBN	9781457703454
DOI	10.1109/ICIST.2012.6221763
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Satellites Computational modeling Predictive models Mobile communication Prediction algorithms Satellite communication Delay
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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