空間調變 (spatial modulation) 的多輸入多輸出(multiple-input multiple-output, MIMO) 系統是在以往振幅與相位 (amplitude/phase) 調變基礎上,將傳送天線本 身也當作傳送資訊的一項調變技術。空間調變解決了以往在空間多工 (spatial multiplexing) 下,隨著天線數量提高而造成的能量損耗問題。同時間, 隨著天 線數量增加,空間調變系統的吞吐量 (throughput) 仍然隨之提高,因此空間調變 技術被視為應用在巨量 MIMO (massive MIMO) 的一項關鍵技術。然而,空間調 變尚有許多待解決之問題:對於行通通訊系統而言,行動裝置上的天線通常礙 於天線理論,只能維持一至二支天線,如果在這樣的條件下使用空間條便技術, 會因其接收多樣性 (receive diversity) 不足而導致錯誤率大幅上昇。另外,在傳 送通道彼此之間有高度相關性時,空間調變技術也不適用。本論文提出一套建 立在空間調變基礎上的新技術——空時排列碼 (Space-Time Permutation Code), 空時排列碼將多個時間點的天線選擇,取其排列順序作為傳送資訊,不同的排 列組合間的差異引出了時間多樣性 (time diversity) ,而時間多樣性解決了以往 空間調變下面臨的問題。此外,空時排列碼如同空間調變,使用天線選擇技術, 維持了低複雜度的接收端設計。空時排列碼還能與其他技術做結合,例如空時
碼 (space-time coding) ,亦或是通道預編碼 (channel precoding) ,借由不同的技 術結合,能使空時排列碼適用於不同的通道環境,或是效能上的提升。在本論 文中,對於空時排列碼的設計進行參數分析,並提供設計範例。而在論文中模 擬並比較空時排列碼與空間調變的表現,從結果中分析並探討空時排列碼實際 效能。

Since the Multiple-Input Multiple-Output (MIMO) system is proposed, the technique becomes popular in the past decade because of the high channel capacity that it ob- tains. The spatial modulation (SM) is proposed, which has additional consideration about the energy efficiency, not only about the spectral efficiency. It means the power consumption of SM-MIMO is reduced in contrast to the spatial multiplexing systems. This thesis proposes a new transmission scheme for MIMO system based on the SM, is called Space-Time Permutation Code (STPC). STPC takes the advantage of the time diversity through the permutation modulation. The antenna selection across several time slots becomes the information for STPC, called permutation array (PA). STPC overcomes some difficult environments such as single receive antenna or highly corre- lated channel, which the conventional SM-MIMO is hard to apply. Moreover, STPC is flexible with the other transmission techniques such as Space-Time Coding (STC). The combination of STPC and STC makes the communication quality more reliable. Sphere decoding (SD) is introduced in this thesis, which is an efficiency decoder in contrast to Maximum Likelihood (ML) detector. And it keeps the decoding method to be optimal. The numerical simulation results present the comparison of STPC and the other trans- mission techniques. It shows that STPC is valuable to study further in the future, and apply in the Massive MIMO.

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