這篇論文討論使用有效的演算法，分配蜂巢式系統中的自由度給特定用戶，再結合反覆式干擾排列以求得最大量的傳輸速率。目前文獻著重在利用有效的干擾排列來增加傳輸速率。另外，現有方式來決定各個用戶可傳輸的資料量也不夠準確。這種方法並沒有考慮到選擇用戶的多樣性以及有效降低對已經選進系統中的用戶所造成之干擾。在這篇論文中，我們提出一些演算法來增加系統之中的用戶量還有盡可能的消除對已在系統中的用戶所產生的干擾。我們也提出一種樹枝狀的近似最佳化演算法，用來決定各個用戶可傳輸的資料量。模擬的結果最後呈現出，提昇傳送資料的用戶數量還有削減已選進系統內的用戶間互相彼此的干擾，可以求得較佳的傳輸速率。

In this thesis, we propose degrees of freedom (DoF) allocation algorithms to distribute data streams among users and combine iterative interference alignment (IIA) to maximum sum rate in cellular system. In previous researches they focus on interference alignment (IA) to improve the sum rate. Besides, the existing user scheduling model which considers overall interference is inaccurate. It takes little attention to both users diversity and minimizes interference of selected users in the cell. In this thesis, we present algorithms to enhance the number of users scheduled in the cell and remove interference to each selected user as much as possible. We also propose near-optimal DoF allocation algorithm with tree-search method. Simulation results are compared to existing users scheduling algorithm and show that the proposed algorithms outperform the conventional approaches in terms of sum capacity.

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