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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/88521


    題名: Resource Management and Beamforming Techniques for Green Wireless Networks
    作者: 林哲瑛;Lin, Che-Ying
    貢獻者: 通訊工程學系
    關鍵詞: 綠能無線通訊網路;波束成型;資源分配;異質網路;無線充電通訊網路;Green Wireless Networks;beamforming;resource management;heterogeneous networks;wireless-powered communication networks
    日期: 2022-01-25
    上傳時間: 2022-07-14 13:52:25 (UTC+8)
    出版者: 國立中央大學
    摘要: 綠色通訊隨著通訊技術發展與環境保護議題的重視逐漸受到關注與討論。節省能
    源與採集能源在無線通訊系統中是兩個主要能改善能源消耗的方式。本文中我們著重
    於綠色環保概念出發探討與設計在兩種網路架構為異質網路,無線充電通訊網路中的
    資源分配和波束成型的議題。在綠色異質網路中,我們探討大型基地台協助小型基地
    台的網路架構中能動態調整的將小型基地台關閉,讓小型基地台流量服務的要求轉移
    至大型基地台來達到節省能源。在大型基地台協助小型基地台的網路架構中節省能源
    的策略包含了很多影響網路能源需求的因素,如: 可用的頻寬、負載使用者的能力、服
    務範圍的大小、使用者的速率要求、中斷機率條件、雜訊干擾等;除此之外,強制中
    斷小型基地台服務的機率也影響到節省能源的決定。在無線充電通訊網路中,我們探
    討在無線網路通訊中讓有採集能源的裝置透過採集電磁訊號轉換成電能儲存或直接使
    用。具體來說,我們在無線傳輸能量的系統下行傳輸時傳輸能量給予多使用者儲存後,
    讓多使用者在上行的傳輸時間利用採集的電磁訊號轉換後的能量傳輸訊息。在透過波
    束成型技術讓基地台能在同時間內讓多使用者在下行傳輸時採集能量,上行傳輸時同
    時傳輸訊息。設計無線充電通訊網路中需考量到能量花費的控制、上行時間多使用者
    同時傳輸的相互干擾、無線傳輸能量的效益與基地台的能量消耗。
    在大型基地台協助小型基地台的網路架構中,設計的問題模型透過條件式馬可夫
    決策模型的線性規劃求解後,得到隨機模型來進行最佳的基地台睡眠與喚醒的策略;
    在無線充電通訊網路中,聯合設計下行與上行的波束成型、下行與上行的時間分配和
    上行時多使用者間的能量控制。其中非凸的最佳化問題,用半正定放寬的方法,先以
    固定的時間分配與上行接收波束成型來求得傳輸能量的解,在透過交替迭代更新後得到最佳的時間分配與上行接收波束成型。最後,提出的設計方法也透過電腦模擬驗證
    效能,經由電腦模擬結果證實論文中提出的馬可夫決策過程的方法在保證強制平均中
    斷機率的前提下可以透過開關小型基地台達到有效率的能源使用,也證實我們提出的
    聯合設計資源分配與波束成型可以有效地節省基地台傳輸能源的能源花費。;Green communication has received significant attention and discussions due to its potential
    telecom business, recent technology advances, and environmental protection. Saving
    energy and harvesting energy are two main perspectives to improve the energy consumption of
    wireless communication networks. In this dissertation, we focus on the green designs for two
    kinds of wireless networks, namely, heterogeneous networks (HetNets) and wireless-powered
    communication networks (WPCNs) from these two perspectives through resource management
    and beamforming techniques. For the green HetNets, we investigate a macrocell-assisted small
    cell network that allows for saving energy consumption by dynamically switching off the deployed
    small cells and offloading the data traffic to the macrocell base station. The power-saving
    strategy of the macrocell-assisted small cell networks depends on several network parameters
    like power consumption of base stations, available bandwidth, user load in the cells, cell size,
    user rate requirement, rate outage probability, and noise power density. Besides, it also affects
    the user dropping probability of the small cells. For the WPCNs, we investigate a wireless
    network that can utilize energy harvesting technology to capture wireless energy and convert
    it into electrical energy that can be used immediately or later. Specifically, we consider that
    wireless-powered devices can harvest energy from radio-frequency signals by the base station
    in the downlink and then utilize the harvested energy for transmitting data in the uplink. The
    base station can concurrently serve multiple users with downlink harvested energy and uplink
    data reception by utilizing beamforming techniques. The designed WPCN, however, suffers
    from several critical issues such as power control, uplink multiuser interference, power transfer
    efficiency, and base station energy consumption.
    For the macrocell-assisted small cell networks, the design problem is formulated as a constrained
    Markov decision process and solved via linear programming. A randomized strategy is proposed to accomplish the optimal sleep/wake-up policy for small cells. For the WPCNs, the
    downlink/uplink beamforming, downlink/uplink time allocation, and uplink multiuser power
    control are jointly designed. The non-convex problem is first solved with fixed time allocation
    and uplink receive beamforming via a semi-definite relaxation (SDR) approach, based on
    which an iterative algorithm is proposed for updating the optimal time allocation and the receive
    beamforming. The proposed design methodologies are validated via extensive computer simulations.
    The simulation results confirm that the proposed Markov decision process approach can
    achieve efficient energy utilization by switching on/off small cells while ensuring the average
    user dropping probability. Also, the simulation results confirm that the proposed joint resource
    management and beamforming scheme can effectively reduce the charging energy consumption
    of the base station.
    顯示於類別:[通訊工程研究所] 博碩士論文

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