在使用天線陣列之多路徑多重輸入多重輸出頻道的無線系統中，多路徑之延遲擴展會造成接收信號間彼此干擾以及導致頻道產生具有頻率選擇的特性。相對於頻道之頻率選擇性，多路徑傳送方向角度的空間增益使得頻道亦具有角度選擇性。根據由路徑延遲以及路徑到達或離開之方向角度所構成的頻道選擇性結構，在本論文中，首先我們將尋求新的觀點，從角度以及頻率方面去探討空間-時間碼與多路徑多重輸出入頻道之間結構的關係。接著，藉由利用多路徑多重輸出入無線頻道的結構，我們提出了一個新的空間-時間碼設計準則。使用電腦搜尋的方式，我們鑑定了新的根據通道結構所設計的空間-時間碼，來證明所提出來新設計準則的可行性。從實驗模擬，也證明了所鑑定出來新的空間-時間碼，在相對應的頻率選擇性頻道裡，它的效能比那些沒有根據頻道結構所設計的空間-時間碼的效能好很多。另外，根據所提出來新的空間-時間碼設計準則，我們提出了兩個隨通道結構調變的空間-時間碼設計系統，所提出來的設計系統不僅低複雜度，而且在信號傳輸錯誤率、信號傳輸資料量以及計算複雜度方面都非常具有彈性。實驗模擬證實了在多重輸出入頻率選擇性的頻道裡，所提出來的隨通道結構調變的空間-時間碼設計系統，它的效能比已經存在的空間-時間碼—比如雅姆提所提出來的正交空間-時間碼—的效能好很多。

此外，進來在消息理論上的發展，證明了在一個無線系統的兩端，使用多根天線陣列可以大幅地提高系統的容量。在傳送端若擁有頻道狀況的訊息，則空間-時間的特徵方向發送系統會是利用此大量系統容量最好的編碼系統。然而，在不穩定的無線頻道環境裡，此編碼系統會因為需要高複雜度多重輸出入頻道訊息的追蹤以及大量頻道狀況訊息的反饋，變得很不實際。因此，藉由利用無線多路徑頻道的結構，我們提出了一個新的空間-時間編碼系統，此編碼系統包含了一個新的以頻道結構為基底做水充填的演算法。藉由蒙地卡羅方法所模擬的中斷系統容量，證明了所提出新的空間-時間編碼系統的效能優越性。

為了能夠更有效的使用頻寬，盲蔽式信號檢測系統吸引了愈來愈多的注意力。在一個不同步的傳輸系統裡，差分相位的編碼系統因為排除了需要做相位同步的問題，所以在不同步的系統裡，它是一個很具吸引力的技術；但是，當頻道變動的很快時，它的效能會大幅度地減低。為了在一個快速變動的無線頻道裡，建立一個可靠的通訊連結，我們提出了一個同時預估不同步頻道及串接渦輪碼信號解碼的低複雜度盲蔽式信號檢測系統。此盲蔽式接收機包含兩個部分︰1)一個卡門濾波器作為其頻道預估的部分以及2)兩個解碼器—一個為差分解碼器，另一個為迴旋碼解碼器—作為其信號解碼的部分。藉由最好可能性所計算的不同軟訊息，在頻道預估器及信號解碼器間反覆的交換，所提出來的系統會預期地達到最好的效能。注意，在所提出的系統裡並沒有訓練的資料，因此對於卡門濾波器，要避免頻道相位不明確的問題是不可能的，但這個問題可由差分解碼器來處理。電腦模擬證實了所提出來的系統在快速變動的頻道環境下，展現了絕佳的強健性。

In a wireless system with multipath MIMO (multiple input multiple output) channels using antenna arrays, the delay spread of multipaths results in intersymbol interference (ISI) and channel frequency selectivity. Similar to the channel frequency selectivity, spatial gains at the multipath angles also naturally result in channel angle selectivity. Based on the channel selectivity structures characterized by the path delays and the path directions-of-departure/arrival (DODs/DOAs), in this thesis, we first seek new insights into the matching of space-time codes and multipath MIMO channels in their angle-frequency (AF) structures. Next, by exploiting the wireless MIMO channel structure, new space-time code design criteria are derived. New structure-based space-time codes are identified through computer searches to justify the new criteria. Simulation results show that these codes have superior performance over the existing codes in the corresponding frequency-selective channels. Based on the new design criteria, we propose two low-complexity channel-adapted space-time (CAST) coding schemes, where trade-offs among codeword error rate, data throughput and computational complexity are very flexible. Simulation results confirm that, in the frequency-selective MIMO channels, the CAST coding schemes can perform significantly better than the existing space-time codes, e.g., Alamouti space-time orthogonal code.

In addition, recent advances in information theory show that employing multiple antennas at both sides of a wireless link promises enormous capacity potential. With knowledge of channel state information (CSI) at the transmitter, space-time eigen-beamforming is the optimum coding scheme to exploit this potential. However, in non-stationary wireless environments, high complexity on MIMO channel tracking and large amounts of CSI feedback render such an approach impractical. By exploiting the wireless multipath channel structure, a space-time coding scheme involving a novel structure-based water-filling algorithm is proposed. Outage capacities evaluated through Monte Carlo simulations confirm the performance advantage of the proposed space-time coding scheme.

For more efficient usage of bandwidth, blind detection schemes attract more and more attention. In a noncoherent system, a differential phase coding scheme is an attractive technique as it obviates the need for phase synchronization. However, its performance degrades considerably when channels vary rapidly. To establish a reliable communication link, we propose a wireless system with a blind receiver which jointly performs noncoherent channel estimation and serially-concatenated turbo code decoding over fast time-varying Rayleigh-fading channels. The low complexity blind receiver consists of two parts: 1) a Kalman filter as its channel estimation part and 2) two decoders, including a differential decoder and a convolutional decoder, as its signal decoding part. With various soft information, calculated in the maximum likelihood sense, iteratively passed around between the channel estimator and the signal decoder, the system is expected to hopefully approach the optimal performance. Note that, with no training data in the proposed system, it is impossible for the Kalman filter to avoid the CSI phase ambiguity problem, which can be perfectly taken care of by the differential decoder. Computer simulations confirm that the proposed system exhibits robustness against fast time-variation of Rayleigh-fading channels.

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