新一代通訊系統 LTE-A (Long Term Evolution-Advanced) 提出載波聚合 (Carrier Aggregation) 技術使得行動裝置 (UE) 可以同時使用多個載波跟演進節點 B (eNodeB) 溝通，由於載波聚合技術聚合多個分量載波 (component carrier)，可以達到更快的傳輸速率，因此近來在行動裝置上使用高頻寬的服務，變得愈來愈可行，像是觀看高解析度的影片，然觀看影片時，使用者最不能接受影片時常停滯或者是解析度過差， 因此，此篇論文將使用者滿意度納入考量。利用影片緩衝長度做為關鍵並將其轉換成可評估使用者經驗 QoE (Quality-of-Experience) 的評定方式。 此篇論文要解決的問題是屬於 NP-hard 難題，因此我們提出一個貪婪演算法 (greedy algorithm) 試圖盡可能最大化使用者滿意度及維持用戶公平性的原則下解決此問題，倘若對使用者在各個載波上加上調變與編碼 (Modulation and Coding Scheme) 的限制， 貪婪演算法甚至可以保證其效能可達到最佳化解法效能的百分之五十。

實驗針對 UE 設置的情景分成兩部分，第一部分研究系統內有固定數量的 UE，實驗模擬結果顯示，所提出的方法在各種情境下的 QoE 效能皆優於其他傳統演算法； 第二部分討論 UE 隨機地進出系統， UE 進入系統一律進到佇列等候，根據我們所提出 的權衡機制， 權衡等候時間或者是資源利用效率，並探討其對系 統整體的影響以及等候時間之公平性，實驗模擬結果顯示，在伺服器維持可接受的 QoE 評定值下，所提出的方法可以使伺服器同時容納最多使用者，並擁有最少的等待時間。

Abstract
Carrier Aggregation (CA) is proposed in LTE-Advanced (LTE-A) to allow user equipments (UEs) and LTE-A base station (evolved NodeB, eNB) communicate through multiple carriers simultaneously. Owing to this technique, services utilizing high bandwidth such as high-resolution video streaming become possible in these days. We study a CA-enabled LTE-A video transmission system providing on-demand video service to multiple UEs and formulate a CA-aware radio resource allocation (RRA) problem using buffer length as the performance metric. Video’s buffer length, which is a key factor of the algorithm, is mapped into the Quality-of-Experience (QoE) indicator. We then propose a QoE-based and buffer-aware downlink scheduling algorithm in LTE-A network. It assigns radio resources efficiently and guarantees a lower bound of performance on average QoE. For the scenario that video streaming requests from UE arrive stochastically, we propose a QoE-based access control mechanism to maintain the service quality while balancing the tradeoff between the waiting time and resource efficiency. Our simulation results show significant improvements in QoE of our algorithm over traditional ones.

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