為了支援高頻寬低延遲的語音服務，近年來巨量天線系統與波束成形 (Beamforming) 的技術已經被廣泛地探討可以強化特定方向的訊號強度並降低對其他方向的訊號干擾以提升系統整體的訊號品質，此論文考慮基地台配置有巨量天線系統並且有大量波束可供基地台選擇的網路情境，我們發現到下行鍊路(Downlink)傳輸時所採用的波束的選擇會直接影響基地台與使用者裝置間的通訊品質，也因此在進行無線資源分配排程(Scheduling)時應同時考慮傳輸時所採用波束的選擇。在本論文中，我們提出兩個波束選擇以及無線資源分配之策略，首先我們定義此網路的最大化吞吐量問題，並且提出可以達到最佳吞吐量之解決方案，接下來為了同時保證最大化吞吐量並滿足服務品質保證的需求我們提出了基於累加懲罰值與封包掉落感知的波束選擇與資源分配方法，所提出的方法在滿足最大化吞吐量的同時亦能夠同時盡可能地使每個 UE 都有較為公平的傳輸機會。模擬結果顯示所提出的的方法確實可以獲得接近於最大化吞吐量方法的吞吐量並在多數場景中都能明確的降低封包被丟棄的機率。

In order to support high-bandwidth and low-latency voice services, in recent years, massive antenna systems and beamforming technologies have been extensively explored to enhance the signal strength in specific directions and reduce signal interference in other directions to improve the overall signal quality of the system. This paper considers the network scenario where the base station is equipped with a huge number of antenna systems and there are a large number of beams for the base station to choose. We found that the choice of the beam used in downlink transmission will directly affect the communication quality between the base station and the user's device. Therefore, the selection of beams used during transmission should be considered when scheduling radio resource allocation. In this paper, we propose two strategies for beam selection and wireless resource allocation. First, we define the maximum throughput problem of this network and propose a solution that can achieve the best throughput. Next, in order to simultaneously ensure maximum throughput and meet the requirements of service quality assurance, we propose a beam selection and resource allocation method based on accumulated penalty value and packet drop perception. The proposed method can maximize the throughput while making every UE have a fairer transmission opportunity as much as possible. The simulation results show that the proposed method can indeed achieve a throughput close to the maximum throughput method and can clearly reduce the probability of packet being discarded in most scenarios.

目錄
第一 章、緒論 1
第二 章、相關文獻 6
2.1 無線資源排程方法 6
2.2 波束選擇方法 7
第三 章、系統模型 9
第四 章、最大吞吐量策略 13
第五 章、機會公平策略 17
第六 章、模擬結果 27
6.1 模擬環境與參數 27
6.2 模擬結果比較對象 29
6.3 系統吞吐量的模擬結果 30
6.4 封包掉落率的模擬結果 31
6.5 傳輸次數的模擬結果 35
6.6 流量負載變化的模擬結果 36
6.7 低延遲封包掉落率的模擬結果 37
第七 章、總結 38
參考文獻 40
附錄­英文論文 43

圖目錄
Fig. 1 系統架構 9
Fig. 2 選擇波束與資源分配之計算流程 12
Fig. 3 在 Case 1 場景中的隨使用者裝置人數變化的吞吐量模擬結果 30
Fig. 4 在 Case 2 的場景中隨使用者裝置人數變化的吞吐量模擬結果 30
Fig. 5 mˆ = 120 時於 Scenes 1 環境下 Case 2 的使用者裝置吞吐量由與傳輸等待時間分布圖 31
Fig. 6 在 Case 1 場景中的封包掉落率模擬結果 32
Fig. 7 在 Case 2 場景中的封包掉落率模擬結果 32
Fig. 8 CBR 主導負載量的 Case 2 場景中 mˆ = 120 時使用者裝置的吞吐量分布 33
Fig. 9 CBR 主導負載量的 Case 2 場景中 mˆ = 120 時使用者裝置的封包傳輸成功率分布 33
Fig. 10 CBR 主導負載量的 Case 2 場景中 mˆ = 120 時使用者裝置的傳輸等待時間由小到大分布 34
Fig. 11 video 主導負載的場景下 mˆ = 120 時使用者裝置傳輸次數分布 35
Fig. 12 Case 3 video 主導負載場景下 mˆ = 100 時 CBR 負載提升引起吞吐量分布集中的變化 36
Fig. 13 Case 4 低延遲封包掉落率 37

表目錄
Table. 1 建立每個使用者裝置對每個波束所回報 CQI 的關係表 10
Table. 2 Table 5.2.2.1­2: 4­bit CQI Table[4] 11
Table. 3 QoS Flow 設置參數 27
Table. 4 QoS Flow 對應封包大小 27
Table. 5 模擬不同流量模式 Case 的參數 28

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