IEEE 802.16m空間多工模式閉迴路多輸出入傳輸之預編碼與等化研究

Abstract

多輸出入傳輸技術近來在行動環境中廣受注目且已經應用在許多數位通訊系統中，因為跟單輸出入傳輸相比之下，容量和可靠度有顯著的提升。 我們聚焦在IEEE 802.16m空間多工模式閉迴路多輸出入傳輸之預編碼與等化研究。本篇論文採用兩種等化方法。第一種為迫零(ZF)等化器，他在頻域上為反向濾波器，這是一個最簡單的等化器，他可以消除符號干擾，但是他會造成雜訊放大。第二種為最小均方差(MMSE)等化器，最小均方差等化器是使設計估測通道信號及實際信號的均方誤差為最小，雖然沒辦法完全消除符號干擾，但是不會造成雜訊放大。 我們依據這兩種等化器，再去設計選擇預編碼的方法。要計算預編碼的話，完整通道資訊必須要傳給傳輸端。這會產生一個問題，因為我們的回傳通道的頻寬是有限的。所以我們預先設計好預編碼，再回傳最合適的預編碼編號。我們提出兩種方法去找尋最適合的預編碼，第一種是基於最小均方差方法，我們把所有預編碼裡代入運算，找出最小均方差。第二種是找出使兩根天線最小的訊號雜訊比最大的預編碼，這個方法必須先計算出每個預編碼天線的訊號雜訊比，我們在找出最適合的回傳。我們會跟以下兩種方法做比較。第一種為基於奇異值的方法，首先把通道頻率響應做奇異值分解，其中通道頻率響應的正交輸入基向量是最佳的迫零等化器，我們把所有可能的預編碼跟他做旋距離計算，找出最小的預編碼回傳。第二種為最佳預編碼計算，我們會利用注水原理去求得最佳解。我們先在加成性白色高斯通道下驗證我們的模擬模型，然後在IEEE802.16m標準下於單路徑和多重路徑通道上模擬。 在本篇論文中，我們首先簡介IEEE802.16m 的標準機制。接著，我們依照標準分別各傳輸下介紹兩種等化器搭配四種選擇預編碼方法並探討其效能。

MIMO channels arising from the use of multiple antennas at both the transmitter and at the receiver have recently attracted significant interest because they provide a significant increase in capacity and reliability over single-input single-output (SISO) channels under some uncorrelation conditions. We focus on Precoding and Equalization for the Spatial Multiplexing Mode of IEEE 802.16m Closed-Loop MIMO. We present two equalizer methods. One is Zero-forcing equalizer. It is an inverse filter in frequency domain. This is the easiest equalizer. It can remove the ISI, but it will increase the noise. The other method is MMSE equalizer. This method is designed to minimize the mean square error of the receive signal and the transmit signal. It can not remove all of the ISI, but it will not increase the noise. A problem associated with precoding is that the channel state information must be known at transmitter. This may be difficult since the bandwidth of the feedback channel is usually limited. Thus, a codebook-based limited feedback precoding scheme is generally used. The main idea is to quantize the precoding matrix and feedback the index of the optimum precoder. We based on these two equalizers to design the selection method to select the best precoder. We proposed MMSE-Based and MaxminSNR-Based method. MMSE-Based method finds the precoder has the minimum mean square error. MaxminSNR-Based method finds the precoder that maximizes the minimum SNR of the two antennas. This method has to calculate each precoder’s antenna SNR. Then, we select the appropriate one to transmit back. We will compare with the following two methods. First is SVD-Based method. We take the singular value decomposition (SVD) of the channel matrix. The right singular vector of the channel matrix is the best ZF equalizer. We calculate all the chordal distance of the possible precoder and the best ZF equalizer. Then, we transmit the precoder. Second is the optimum precoder computation. We use water-filling method to get the solution. We verify our simulation model on AWGN channel and then do the simulation on singlepath and multipath channels for IEEE 802.16m. In this thesis, we first introduce the standard of the IEEE 802.16m. Then we describe the precoding and equalization methods we use and discuss the performance in each transmission condition for IEEE 802.16m.