%0 Journal Article
%A LI Hong-yan
%A MA Jian-peng
%A SUO Long
%A WANG Kan
%A ZHOU Mo-miao
%T Kalman Filter-Based Prediction for Interference Alignment
%D 2017
%R 10.13190/j.jbupt.2017.01.016
%J Journal of Beijing University of Posts and Telecommunications
%P 89-93
%V 40
%N 1
%X The impacts of both noise and time-variation of channels on interference alignment in the <em>K</em>-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.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2017.01.016