在認知無線電(CR)網絡中的信息安全性和能效已經得到了廣泛的研究。然而，到目前為止，在底層頻譜共享機制下的CR網絡中，具有多個不可信的次級用戶(SU)的情況尚未被研究；因此本文研究了這種場景中多輸入單輸出CR網絡的下行鏈路保密節能協調波束成形設計。本文的目標為滿足主要用戶(PU)和SU的傳輸速率要求，以及對主要發射機(PTx)和次級發射機(STx)功率預算的約束下，最大化全局保密能效(GSEE)，其定義為所有PU的保密率總和與總功耗的比率。為了解決非凸GSEE最大化(GSEEM)問題，我們提出了一種基於Dinkelbach方法和successive convex approximation(SCA)算法來聯合優化PTx和STx的波束形成向量；並且分析了所提出的GSEEM算法的收斂行為和計算複雜度，接著探討了與保密率最大化設計和功率最小化(PM)設計下GSEE的關聯。鑑於所提出的GSEEM算法的計算複雜度明顯高於PM設計，因此進一步設計了一種兩步驟搜索方案，以基於PM設計和黃金搜索方法，有效地搜GSEEM問題的近似解。仿真結果證明了所提出的GSEEM算法和搜索方案的有效性，並顯示空間自由度（主要由PTx和STx的天線數量決定）是所提出的GSEEM算法性能的關鍵因素。

The information security and energy efficiency in cognitive radio (CR) networks have been extensively studied. However, the practical scenario involving multiple untrusted secondary users (SUs) in CR networks under the underlay spectrum sharing mechanism has not been studied so far. This thesis considers the downlink secrecy energy efficient coordinated beamforming design for multiple inputs single output CR networks under this scenario. Our goal is to maximize the global secrecy energy efficiency (GSEE), defined as the ratio of the sum of secrecy rates of all the primary users (PUs) to the total power consumption, under requirements on transmission rate of PUs and SUs as well as constraints on power budget at the primary transmitter (PTx) and the secondary transmitter (STx). To tackle the non-convex GSEE maximization (GSEEM) problem, an algorithm is proposed based on Dinkelbach method and successive convex approximation to jointly optimize beamforming vectors of the PTx and the STx. The convergence behavior and the computational complexity of the proposed GSEEM algorithm are analyzed, followed by the connection with the secrecy rate maximization design and the power minimization (PM) design in terms of GSEE. In view of significantly higher computational complexity of the proposed GSEEM algorithm than that of the PM design, a 2-step searching scheme is further designed to efficiently search for an approximate solution to the considered GSEEM problem based on the PM design and the golden search method. Simulation results demonstrate the efficacy of the proposed GSEEM algorithm and the searching scheme, and show that the spatial degrees of freedom (primarily determined by the antenna numbers of PTx and STx) is the key factor to the performance of the proposed GSEEM algorithm.

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