利用於時間相關多輸入多輸出之為源分配預測編碼

Abstract

In this thesis, adaptive rate transmission for time-correlated MIMO channels with limited feedback is considered. The number of bits allocated to each subchannel of MIMO system is dynamically adapted according to the current channel condition and predictively coded for feedback. Assuming the channel is a first-order Gauss-Markov random process, the optimal prediction is derived for the next bit allocation (BA) and the corresponding prediction error variance is analyzed for slowly varying channel. Using the prediction error variance, the quantizers of the prediction errors can be adapted to get a smaller quantization error. Furthermore, we show that the prediction error variance depends only on the time correlation coefficient. This leads to the conclusion that a codebook designed for a particular time correlation coefficient can be easily modified to a codebook for different correlation coefficient without redesign. Simulations are presented to demonstrate that the proposed predictive coding can achieve a very good approximation of the desired transmission rate with a very low feedback rate.

In this thesis, adaptive rate transmission for time-correlated MIMO channels with limited feedback is considered. The number of bits allocated to each subchannel of MIMO system is dynamically adapted according to the current channel condition and predictively coded for feedback. Assuming the channel is a first-order Gauss-Markov random process, the optimal prediction is derived for the next bit allocation (BA) and the corresponding prediction error variance is analyzed for slowly varying channel. Using the prediction error variance, the quantizers of the prediction errors can be adapted to get a smaller quantization error. Furthermore, we show that the prediction error variance depends only on the time correlation coefficient. This leads to the conclusion that a codebook designed for a particular time correlation coefficient can be easily modified to a codebook for different correlation coefficient without redesign. Simulations are presented to demonstrate that the proposed predictive coding can achieve a very good approximation of the desired transmission rate with a very low feedback rate.