使用位元配置之預測量化與子載波分群應用於時間相關性多輸入多輸出正交分頻多工系統之回授

Abstract

In the thesis, we consider MIMO-OFDM system over time correlated multipath fading channel with limited feedback. The transmission rate is adapted according to the channel condition. Assume the taps of multipath fading channel are i.i.d. and correlated in time, we can model each tap as a first-order Gauss-Markov process. We show that the frequency domain channel on each subcarrier is still first-order Gauss-Markov process. We apply predictive quantization of bit loading method to take advantage of the time correlation. Furthermore, we consider subcarrier clustering, in which the subcarriers are grouped into clusters and we feedback only one bit loading vector for each cluster. Subcarrier clustering allows us to take advantage of the frequency correlation of the MIMO channels. Compared with the previous works that only utilize the frequency correlation on MIMO-OFDM system, the proposed method has a better performance when the channel is varying slowly.

In the thesis, we consider MIMO-OFDM system over time correlated multipath fading channel with limited feedback. The transmission rate is adapted according to the channel condition. Assume the taps of multipath fading channel are i.i.d. and correlated in time, we can model each tap as a first-order Gauss-Markov process. We show that the frequency domain channel on each subcarrier is still first-order Gauss-Markov process. We apply predictive quantization of bit loading method to take advantage of the time correlation. Furthermore, we consider subcarrier clustering, in which the subcarriers are grouped into clusters and we feedback only one bit loading vector for each cluster. Subcarrier clustering allows us to take advantage of the frequency correlation of the MIMO channels. Compared with the previous works that only utilize the frequency correlation on MIMO-OFDM system, the proposed method has a better performance when the channel is varying slowly.