多用戶正交分頻多工系統(MU-OFDM)被視為未來蜂巢及無線區域網路上的一項重要技術，它可達到高的傳輸資料量且允許多用戶在不同的載波上同時傳輸資料。MU-OFDM的資源分配是指用戶之間的子載波和功率分配。一個有效的資源分配方式可以提高頻譜的使用效率以及整體的服務品質。
在先前的資料中，已有提出有效的資源分配方法提高整體傳輸的資料量，但是卻不能確保用戶之間的公平性。在本論文中，我們提出一種新型且具有低複雜度的方法來實現多用戶之間的資源分配問題。討論在有限的傳輸總功率下如何達到最高傳輸的資料量，並維持用戶之間傳輸資料量的公平性。然而最佳的分配法和利用遞迴式解根的方法其複雜度頗高，所以我們提出一種較低複雜度的方法，一樣也可以維持用戶之間傳輸資料量的公平性。
我們提出的方法是將有限的總功率分成兩個部份，其中一個部份用於子載波的分配，另一個部份用來調整用戶間傳輸資料量的公平性，也就是將功率分配給當時擁有最小的資料量比例(實際傳輸資料量除以預設傳輸資料量比)的用戶。每次都將功率分配給當時擁有最小的資料量比例的用戶使得用戶之間的差距越來越小，也就達到了用戶之間的公平性了。
如何將總功率做最有效的分配，與決定用於載波分配部分所需要的功率以及用於彌補擁有最小的資料量比例的用戶所需要的功率該用多少，也是本文探討的重點之ㄧ並且提供推導的分析結果。
最後的模擬結果顯示運用提出的方法不但維持用戶之間傳輸資料量的預設比例(公平性)，也達到了最佳的方法所達到的傳輸量的98%，證明此方法的可行性。

Multi-user orthogonal frequency division multiplexing (MU-OFDM) allows multiple users to transmit simultaneously on different subcarriers during the same symbol period and which is a promising technique for achieving high downlink capacities in future cellular and wireless local area network systems. The resource allocation of MU-OFDM is the subcarrier and power allocation among users sharing the same OFDM spectrum. An efficient resource allocation algorithm can improve the spectrum efficiency and support the quality of service requirement.
In the previous literature, some resource allocation algorithms cannot ensure the fairness among users in advance. This thesis considers an allocation scheme of subcarriers and power to each user for maximizing the sum of users’ data rates, and subjecting to constraints on the total transmit power and proportional fairness among users’ data rates. Since the computational complexity of optimal solution and iterative root-finding method for achieving the constraints are extremely high, we propose a low-complexity suboptimal algorithm to satisfy the constraints. In the proposed algorithm, we divide the total transmit power into two parts such that a portion of the total power uses in the subcarrier allocation algorithm for attaining the coarse proportional fairness and the rest power is used in the power allocation algorithm for increasing minimum proportional data rate and fulfilling the better proportional fairness. Additionally, a range of deciding how much the power will be allotted to the subcarrier allocation algorithm is also derived. The simulation results demonstrate that the proposed algorithm can satisfy the proportional fairness and achieve about upward 98% capacity of the optimal power algorithm in [11].

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