頻帶內全雙工架構以其在頻譜效益上的優勢使其成為當代無線通訊系統的關鍵技術之一。然而因為其同時使用相同頻段進行傳輸與接收，接收時會收到自干擾訊號，而導致接收訊號品質的急遽下降，因此依賴自干擾消除技術消除自我干擾訊號。傳統自干擾消除技術通常為估測自干擾訊號通道後還原訊號。近年文獻指出獨立成分分析法被認為是頻帶內全雙工架構中的有效的自干擾消除技術，其利用訊號獨立與其分布為非高斯之特性來分離自干擾訊號並加以消除。本論文探討基獨立成分分析法之頻帶內全雙工自干擾消除技術。本論文提出了一種新的架構，假設頻帶內全雙工架構中的非線性雜訊為一獨立訊號源，並利用獨立成分分析法分離非線性雜訊，進一步將獨立成分分析法訊號分離架構的效能進行提升。為了確認所提出的方式可行，我們計算出訊號間的獨立關係，用以證明非線性訊號可以為當成是一獨立訊號源。實驗結果表明，在非線性程度較大時，我們所提出的架構與原始獨立成分分析法架構相比存在10dB的差異。另外，有鑑於獨立成分分析演算法在疊帶階段使用梯度下降法的疊帶次數過高、導致多於的計算複雜度。本文也相應提出一種以動量為基礎的獨立成分分析演算法，相較於傳統方法，我們利用動量會參考過去更新方向的特性降低迭代次數以及計算複雜度。另一方面，我們將此概念應用在3種不同獨立成分分析演算法中。實驗結果表明，所提出的演算法在性能相近的情況下，可以降低約88\%的計算複雜度。

In-band Full Duplex (IBFD), with its advantages in spectrum efficiency, has made it one of the recent focuses of 5G wireless communication systems. However, its transmission and reception frequency band are the same, IBFD systems receive self-interference signal when receiving. As a result, successive interference cancellation (SIC) technology is required to solve this problem. The conventional SIC method usually recovers the SI signal after estimating the SI channel. On the other hand, in recent years, literature has pointed out that independenr component analysis (ICA) approach can be considered as a new SIC scheme in IBFD systems. This scheme employs characteristics of signal independence and non-Gaussian distribution to separate interference signals. In this thesis, a novel architecture is proposed which assumes that the nonlinear noise in the IBFD architecture is an independent signal source, and ICA technique is used to separate the nonlinear noise. The
proposed architecture will improve the performance even more than the conventional architecture. In order to verify that the proposed method is feasible, we calculate the independent relation between source signals to prove that the nonlinear signal can be regarded as an independent signal source. The experiment result shows that the proposed architecture delivers a 10dB enhancement when the degree of nonlinearity is large. In addition, in view of excessive number of iterations and redundant computational complexity of the gradient descent method used by ICA, this thesis proposes a momentum-based ICA, which uses the characteristics of momentum to reduce the number of iterations and computational complexity. Furthermore, we apply this concept to three different ICA algorithms. The simulation results show that the proposed algorithm can reduced about 88\% of computational complexity while in the the case of similar performance.

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