近年來，IEEE 802.11無線區域網路的基礎設施和行動 /手持設備日益地普及並且被廣泛應用。在許多公共場所已經提供IEEE 802.11 無線區域網路，例如圖書館、捷運站和大學校園，這些設置無線區域網路AP的地點，我們稱之為熱點。越來越多的智慧型手機上市，這使得人們可以較以往以快速的方式上網。基本上，IEEE 802.11無線區域網採用的是基礎設施模式，它包含了一個存取點當作行動用戶和網路伺服器之間的橋梁。然而，在IEEE 802.11媒體存取控制層採用一個以競爭為基礎的通道存取的機制，稱為分散式協調功能。在分散式協調功能之下，所有IEEE 802.11的節點，包括AP和移動用戶傳送封包都有相同的通道傳輸機率。在無線網路中，這樣的行為導致了下載吞吐量嚴重降低。在這篇論文中，我們提出了一個跨層式自適應演算法，在AP的媒體存取控制層動態調整最小競爭視窗，根據上傳和下載之間平均傳輸的吞吐量和通道環境的變化，完成每個服務流傳輸的公平性。在上傳和下載傳輸對於應用類型有不同的傳輸頻寬需求的情況，我們的演算法根據上傳及下載之間不同的傳輸頻寬需求可以有效地找到適當的最小競爭視窗，提供權重式的公平。實驗結果證明我們的方法在不同且時變的無線網路環境中，可以有效地提供每個服務流的公平性和權重式的公平性。

In recent years, IEEE 802.11 Wireless Local Area Networks (WLANs) have become increasingly popular with the wide deployment of infrastructures and the prevalence of mobile/handheld devices. Many public areas have been providing IEEE 802.11 WLANs such as library, metro station and campus where are called hot spot. More and more smart-phones were sold, it makes many people now can easier and quickly access the Internet than before. Basically, IEEE 802.11 WLANs employ an infrastructure mode in which an Access point (AP) acts as a bridge between mobile stations and network servers of wired domain. However, IEEE 802.11 Medium Access Control (MAC) layer employs a contention-based channel access mechanism, named Distributed Coordination Function (DCF) for its distributed and simple manner. With DCF, all IEEE 802.11 nodes with packets to send including AP and each mobile station generally have the same channel-access probabilities. In the wireless networks, it leads to a momentous throughput degradation of downlink. In this thesis, we propose a cross-layer adaptive algorithm which dynamically adjusts the minimum contention window size (CWmin) in MAC layer of AP, according to the average ratio between downlink and uplink throughput and channel environments to achieve per-flow fairness. In case that uplink and downlink transmissions are with different bandwidth demands for various applications, our algorithm also can efficiently find the suitable CWmin which provides weighted fairness based on their resource requirements. The simulation results demonstrate that our scheme can effectively provide both per-flow fairness and weighted fairness in a diverse and time-varying WLAN environment.

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