MAI和Near-far effect是在分碼多工進接(CDMA)系中中傳統接收器效能受限的兩個主要因素，而為了解決這兩個問題，干擾控制技術和功率控制演算法為兩個被設計用來解決此問題的方案。S. Ulukus與R. D. Yates提出了結合了最小均方差干擾抑制及功率控制技術的方法，稱為最小均方差功率控制技術(MMSE power control)。為了降低最小均方差功率控制技術中所使用到的運算複雜度，C. L. Wang等人提出了使用適應性干擾抑制取代原本架構中的估算濾波器係數的MMSE演算法。從電腦模擬中，由於適應性干擾抑制濾波器要收斂到最小均方差干擾抑制濾波器之濾波器係數須要一段時間，此法會在收斂過程中會須要較多的功率消秏以彌補在濾波器效能上的差異。在本論文中，我們藉由討論上面兩種方法的主要差異點，研究出何以後者會使用較多的功率消秏，並討論適應干擾抑制濾波器和功率控制技術兩者的互相影響，針對這個特點，我們分析並提出一簡單的二階迴歸模型來計算在適應性濾波器中干擾均分差，並預期其效果，再將此結果送入功率控制演算法中，如此能使具有適應性干擾抑制之功率控制系統有更接近最小均方差功率控制技術之效能。此外，為進一步提升適應性干擾抑制濾波器的效能，我們提出一簡單之應用於適應性濾波器中可變式步進值(step size)的調整方法。
從電腦模擬的結果，我們發現，利用以上兩種改良式的方法，能在不論是總消耗功率上，或是收斂速度上，有著更接近最小均方差功率控制技術之效果，而同時，此所提出的演算法所增加的複雜度並不大。我們可以相信，此方法較原本結合適應性干擾抑制及功率控制之作法，具有更佳的效能。

The capacity of a code division multiple access (CDMA) system is limited by multiple access interference (MAI) and the near-far effect. Interference suppression and power control provide solutions to these problems. In some previous works, interference suppression and power control are considered separately. In order to increase the system capacity of a CDMA system, it is better to have a joint consideration of these two issues. Ulukus and Yates proposed an iterative and distributed algorithm that is able to achieve this goal. It is shown that this approach can converge to a minimum power solution where all users satisfy their own quality of service requirement; besides, the corresponding filter coefficients also converges to the minimum mean-squared error (MMSE) solution. Recently, Wang et al. have developed a strategy to reduce the high computational complexity involved in the algorithm proposed by Ulukus and Yates. The reduction of computational complexity comes from the use of an adaptive algorithm instead of the instantaneous MMSE approach for interference suppression. In this thesis, we further analyze the adaptive approach proposed by Wang et al and propose an improved scheme for power control with interference suppression. As compared to the approach by Wang et al., the proposed one achieves better performance (in terms of both convergence speed and power consumption) with no significant increase in complexity. Computation simulations are given to demonstrate the effectiveness of the newly proposed approach.

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