在多天線系統下使用Kalman濾波器之Tomlinson-Harashima 前置編碼設計

Abstract

In this thesis, we study the problem of combining Kalman filter for channel tracking and Tomlinson-Harashima precoding for channel equalization in MIMO systems. The multiple-input multiple-output (MIMO) Tomlinson-Harashima precoder (THP) is a well known equalization structure for mitigating inter-stream interference in fading MIMO systems, which is the application of “dirty paper coding“ and can reserve the channel capacity. Kalman filter is an estimator based on the conception of random process, compare to other estimators, Kalman filter collects all previous channel information for estimating, yet the other estimators estimate the variables by considering the present observation. THP is optimal by assuming perfect channel state information (CSI) at both transmitter and receiver. However, this assumption is not achievable in real world. In this work, under the assumption of partial channel state information (P-CSI), we use Kalman estimation for channel tracking and combine the estimation into THP optimization which considers the channel estimation error. In simulation results, we compare the proposed approach with earlier works and can show that the performance (BER) of THP system with Kalman estimation (THP-Kalman) for channel tracking is superior to THP with linear-minimum-mean-square-error (LMMSE) estimator (THP-LMMSE) in time-division-duplex (TDD) system. Besides, we also compare the computation complexity of THP-Kalman and THP-LMMSE. By changing the Doppler rate (the parameter of mobility), THP-Kalman performs more flexible, while THP-LMMSE is sensitive to the varying rate of channel.