卡尔曼预测在干扰对齐中的应用

Kalman Filter-Based Prediction for Interference Alignment

分析了K用户干扰信道中,收发端的噪声和信道的时变特性对干扰对齐实际性能的影响,并提出一种基于卡尔曼预测的信道状态信息修正方法,以改善干扰对齐的性能.该方法利用信道的时域相关特性对信道增益进行跟踪预测,并通过预测值对估计值进行修正,从而提高发送端获取信道状态信息的精度.仿真结果表明,所提出的修正方法降低了信道增益估计值的均方误差,有效地改善了干扰对齐的性能,提升了系统的和速率.

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.