Kalman Filter-Based Prediction for Interference Alignment

doi:10.13190/j.jbupt.2017.01.016

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2017, Vol. 40 ›› Issue (1): 89-93.doi: 10.13190/j.jbupt.2017.01.016

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Kalman Filter-Based Prediction for Interference Alignment

ZHOU Mo-miao, LI Hong-yan, WANG Kan, SUO Long, MA Jian-peng

School of Telecommunications Engineering, Xidian University, Xi'an 710071, China

Received:2016-08-23 Online:2017-02-28 Published:2017-03-14

Abstract

Abstract: The impacts of both noise and time-variation of channels on interference alignment in the K-user interference channel were analyzed. To revise the channel state information at transmitters, a Kalman filter-based algorithm was proposed. First, tracking prediction on channel coefficients is made based on the temporal correlation between them. Then, by combining the estimated value and the predicted value, a more accurate value of channel gain is obtained. Simulations reveal that the proposed algorithm can reduce the mean square error of channel estimations and thus improve the sum-rate of the system.

Key words: interference alignment, channel state information, predicting, sum-rate

CLC Number:

TN929.5

ZHOU Mo-miao, LI Hong-yan, WANG Kan, SUO Long, MA Jian-peng. Kalman Filter-Based Prediction for Interference Alignment[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(1): 89-93.

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Kalman Filter-Based Prediction for Interference Alignment

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