本篇論文提出覆蓋式感知傳收機設計。該系統包含主要使用者及次要使用者共存在同一個網路，其中主要使用者允許次要使用者以合作式中繼放大轉發主要使用者訊號，同時傳輸次要使用者的訊號。由於我們的傳收機設計，主要目標在次要使用者的傳送端做預編碼設計。然而，預編碼設計需在傳送端知道完美通道狀態資訊，於實際系統並不可行。所以於本論文中，我們考量一種不完整通道迴授機制，稱為隨機向量量化通道迴授機制，回傳量化通道方向資訊給次要使用著傳送端。由於量化通道方向資訊將會有量化誤差，所以我們首先考量量化誤差的統計特性，於線性最小均方誤差接收機之下，推導出對應於主要使用者及次要使用者的最小均方誤差的解析解。其後，根據此均方誤差的統計結果，我們提出兩種強韌式的設計準則：第一種是在保證主要使用者以及次要使用者的服務質量之下，最小化次要使用者傳送端的功率；第二種是在保證主要使用者的服務質量以及次要使用者傳送端滿足功率消耗限制之下，最小化次要使用者的均方誤差。由於兩種方法皆非凸函數，欲求出全域解是有困難的。因此我們提出一種疊代的方法，把原本的兩種最佳化問題皆分為兩個子問題，再分別交替疊代求其解。模擬結果驗證了我們的兩種設計方法確實有達到強韌式設計。

In this thesis, we propose cognitive overlay transceiver designs, where a primary transceiver pair and a secondary transceiver pair coexist in a network and the primary user (PU) allows the secondary user (SU) to transmit concurrently its signals at the price of reducing the power of the PU’s signal relayed by cooperative amplify-and-forward (AF). Since the considered transceiver design is mainly to devise the precoders both for the PU and the SU at the secondary transmitter (ST), the channel state information (CSI) has to be known at the ST. We therefore consider the limited feedback scheme with the random vector quantization (RVQ), where the ST can only know the quantized channel direction information (CDI). Considering the statistics of the CSI quantization error and the linear minimum mean-squared error (LMMSE) receiver, we derive the closed-form MSE expressions corresponding to the PU and the SU. With the derived MSEs, we propose two robust design criterions. One is to minimize the ST’s power consumption under the constraint that the PU’s and SU’s quality-of-service (QoS) (i.e. MSE) can be met. And the other is to minimize the SU’s MSE when the PU’s QoS can be controlled under a certain value and the ST satisfies the limitation of its transmission power consumption. Both the optimization problems of the proposed design criteria are not convex and the corresponding solutions cannot be obtained directly. We then propose to transfer the original optimization problems into two sub-problems, where each of them is eventually formulated as a convex optimization problem and the solutions are obtained iteratively, which is effective. Thus, the results can be obtained with the interior-point method. Simulations certify the robustness of our designs.

[論文審定書+i]
[誌謝+ii]
[中文摘要+iii]
[英文摘要+iv]
[目錄+v]
[圖次+vi]
[表次+viii]
[第1章 序言+1]
[第2章 系統模型+9]
[第2.1節 隨機向量量化系統模型+9]
[第2.2節 隨機向量量化通道的均方誤差+12]
[第3章 隨機向量量化通道回授機制下強韌式傳收機設計+16]
[第3.1節 最小化次要使用者傳送端的功率消耗+16]
[第3.2節 最小化次要使用者均方誤差+21]
[第3.3節 通道狀態資訊回授探討+24]
[第4章 系統模擬及分析探討+26]
[第5章 結論與未來展望+39]
[參考文獻+40]
[附錄A+43]
[附錄B+46]
[附錄C+49]

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