在本論文中，我們考慮兩種不同架構的無線充電通訊網路(wireless powered communication networks, WPCNs)。第一種架構的無線充電通訊網路中，考慮兩個單天線的無線網路基地台(access point, AP)和一個單天線使用者在多個傳輸時槽(time slot)的情況下，進行能量與訊息的傳輸；第二種架構則是只在單一傳輸時槽的情況下，考慮兩個多天線的無線網路基地台、多個單天線的使用者以及能量波束成型(energy beamforming)、接收波束成型(receive beamforming)的設計。在第一種架構中，我們欲利用衰減通道中的時間多樣性來最佳化整個系統的傳輸量。首先，在假設所有通道狀態資訊(channel state information, CSI)為事前已知的情況之下，此最大化系統傳輸率的問題可以被轉換為一個凸優化的問題(convex problem)且可以有效率地被解決。然而，在實際的系統中，必須考慮通道狀態資訊有因果性的限制，因此，透過轉換此最大化系統傳輸量問題為一個最大化系統的能量效率的問題後，我們在本論文中提出接近實際系統的即時演算法(online algorithm)。除此之外，我們更進一步地提出具有低複雜度並且可以有效率地實現此實時演算法的方法。在第二種架構中，為了提升使用者的資訊傳輸量以及對抗雙倍的遠近現象(doubly-near-far phenomenon)，透過聯合最佳化下行(downlink, DL)-上行(uplink, UL)的時間配置、能量波束成型、上行傳輸的功率配置和接收波束成型，我們欲最佳化所有使用者中最小的資訊傳輸率。我們提出一個有效率的連續逼近法(successive approximation method)來解決此問題，透過我們提出的連續逼近法所得到的近似解幾乎與具有高運算複雜度的全域最佳解(global optimal solution)有相同的性能表現。

In this thesis, we consider two different scenarios of wireless powered communication
networks (WPCNs). The first one is a WPCN with two single-antenna access points
(APs) and a single-antenna user, where energy and information transfer over multiple
time blocks is considered; the other is with two multiple-antenna APs and K
single-antenna users, where energy beamforming and receive beamforming designs are
considered. For the first scenario, we aim to maximize the system throughput by exploiting
time diversity of fading channel. Under an ideal assumption that the channel
state information (CSI) are known a priori, the throughput maximization problem
can be reformulated as a convex problem, and hence can be optimally solved. Considering
the practical causality constraint on CSI, we propose an online algorithm based
on reformulating the throughput maximization problem as an energy-efficiency maximization
problem. We further present an efficient implementation for the proposed
online algorithm to reduce the computational complexity. For the second scenario, to
maximize the users’ rate and overcome “doubly-near-far” phenomenon, we maximize
the minimum rate among the users by jointly optimizing downlink(DL)-uplink(UL)
time allocation, energy beamforming, UL power control and receive beamforming.
We propose an efficient successive approximation method for handling this problem
and get an approximation solution which has nearly optimal performance compared
to the global optimal solution of the state-of-the-art algorithm, which is of high computational
complexity.

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