本篇論文中，我們將針對以空間頻率格子碼為基礎的多重輸入單一輸出正交

分頻多工通訊系統，探討如何利用殘存路徑處理結合卡門濾波器在頻率選擇性時

間變化塊狀衰減的通道模型中作通道估測。在傳輸端，先由迴旋碼編碼器對資料

位元流做編碼，接著經過解多工器將迴旋碼對映到星座點，並收集所需要的資料

長度後再經由正交分頻多工調變並傳送之。在接收端，首先利用己知的訓練序列

得到卡門濾波器的通道估測初始值，並由殘存路徑處理結合卡門濾波器追蹤通道

狀態並且更新其通道估測值。藉由所得之估測結果利用通道頻域响應各子載波彼

此間的相關性作最小均方差，進一步的使得通道估測誤差值達到最小。解調端可

利用殘存路徑處理卡門濾波器所估測的通道增益經由維特比演算法解碼出資訊

位元。

In this thesis, a Kalman filter (KF) with per-survivor processing (PSP) is

addressed for space-frequency trellis codes in MISO OFDM systems over frequency

selective time varying block fading channel model. The data stream is first encoded

by a convolutional encoder, followed by a demultiplexer, which maps the output of

convolution encoder into a constellation point. Then, collecting the length of

information needed, finally, it is modulated by OFDM before transmission. At the

receiver, utilize the own training sequence that known to get the initial state value of

channel of Kalman filter. And via the per-survivor process with Kalman filter,

tracking the state and update estimating the value of channel. Using the property of

the correlation of sub-carrier, minimum mean-square error sense can provide more

precise of estimation error. The demodulation end can utilize the result of PSP-KF to

decode information bit via Viterbi-algorithm

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