空間調變是一種特殊型態的多天線傳輸技術，其優勢是只需要一個射頻鏈。近年
來，一個全新型態的交互零相關區間互補序列對被提出作為空間調變的調校序列。
由於它的相關函數具有一個特別的零相關區間性質，在頻率選擇性通道上可以達到
最佳通道估測性能。在文獻中，此一序列對大多數的建構方法皆由已知的格雷互補
序列對所建構，只有一種方法是基於布林函數建構。然而，由布林函數建構之交互
零相關區間互補序列對的長度也非常受限。在此篇論文中，我們提出了交互零相關
區間互補序列對的新穎布林函數建構方法，可以建構出具彈性長度且擁有更大零相
關區間寬度的交互零相關區間互補序列對。另一方面，交互零相關區間互補序列對
的零相關區間寬度有理論上的限制。而在此篇論文中，我們擴展到交互零相關區間
互補序列集合，因此具有更大的零相關區間寬度，可用於空間調變調校序列以對抗
更大的通道傳播延遲。在此篇論文中，我們提出了多個交互零相關區間互補序列集
合的建構方法，其具有更大的零相關區間寬度與彈性的長度。我們甚至可以建構出
所謂的完美交互零相關區間互補序列集合，其零相關區間寬度可達到理論的最大
值。接著，我們根據所建構的交互零相關區間互補序列集合提出了一個新穎的調校
架構用於空間調變系統。從通道估測效能的模擬結果中可以看到，所提出的調校序
列可以容忍更大的通道傳播延遲，甚至可以達到最低的均方誤差，大幅提高通道估
測性能。

Spatial modulation (SM) is one special type of multiple-input multiple-output (MIMO) technique whose advantage is that only one radio-frequency (RF) chain is needed. Recently, the so-called cross Z-complementary pair (CZCP) was proposed as the SM training sequence. Optimal channel estimation performance over frequency-selective channels can be achieved since the CZCPs have the specific zero correlation zone (ZCZ) for autocorrelation and crosscorrelation sums. In the literature, most constructions of CZCPs are based on existing Golay complementary pairs (GCPs); only one method is based on Boolean functions. However, the length of CZCPs from Boolean functions is very limited. In this thesis, a novel construction of binary CZCPs based on Boolean functions is proposed. The proposed construction can generate CZCPs with more flexible lengths and large ZCZ widths. On the other hand, the ZCZ width of the CZCP is theoretically upper bounded by half sequence length. In this thesis, the CZCP is extended to the cross Z-complementary set (CZCS) to have larger ZCZ width which can be used in SM to combat larger delay spread. Several generic constructions of CZCSs with large ZCZ widths and flexible lengths are proposed in this thesis. Even the perfect CZCS, whose ZCZ width has the maximum value, can be obtained. Numerical simulations
demonstrate that the proposed CZCS-based training sequence can tolerate a larger delay spread to improve the channel estimation performance in SM.

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