功率放大器為達到最佳的功率效益，大多操作在接近飽和區的地方，但是會受到嚴重的非線性響應，造成訊號失真，以及頻譜增生，對鄰近通道產生干擾；為了追求功率效益並維持系統的線性，主要有兩個研究方向，第一是改善電路設計，發展更進階的功率放大器，第二是透過訊號處理，延長功率放大器之線性區，又稱為線性化技術，另外，在高功率寬頻的系統下，記憶效應的影響也不再能被忽視。本論文結合峰值因數削減方法與數位預失真器，發展適用於具有記憶效應之寬頻功率放大器線性化技術，峰值因數削減方法為降低訊號峰均比之技術，數位預失真器則是於數位基頻中將傳送訊號預先做適當的補償，使功率放大器之輸出更線性。我們基於直接學習結構，發展結合廣義記憶多項式模型與網格搜尋之數位預失真器演算法，並與記憶多項式模型搭配查詢表的演算法，透過實際量測比較其效能，量測結果顯示廣義記憶多項式/網格搜尋的效能稍微優於記憶多項式/查詢表，但是有執行時間過長的缺點。我們也加入峰值因數削減方法，在進行數位預失真之前，先對訊號作峰值因數削減，量測結果顯示結合此兩種技術搭配使用能進一步降低對鄰近頻道的干擾，但會造成訊號額外的失真。

In general, the RF power amplifier (PA) works near the saturation region to achieve maximum power efficiency. However, PA’s nonlinear response near the saturation region results in signal distortion and spectral regrowth that interferes with adjacent channels. To achieve a high power efficiency and maintain the linearity, there are two research directions. One is to improve circuit design and develop advanced PA architectures, and the other is to extend PA’s linear region by linearization techniques. Besides, the memory effect can not be ignored in the high-power, wideband system. In this thesis, we combine the crest factor reduction (CFR) technique and digital predistortion (DPD) to develop the linearization technique for wideband PAs with memory effect. The CFR technique reduces the peak-to-average power ratio (PAPR) of the signal, while DPD pre-compensates the transmitted signal in digital baseband so that the PA output has a linear behavior. Based on the direct learning architecture, we use the generalized memory polynomial (GMP) model and grid search to develop the DPD algorithm. The experimental results show that, compared with the direct learning DPD algorithm that is based on the memory polynomial (MP) model and the look-up table method, the proposed DPD algorithm has a better performance in adjacent channel leakage ratio (ACLR), but is much more time-consuming. In addition, we use the clipping and filtering technique to reduce the PAPR of the transmitted signal prior to DPD. The experimental results show that it further improves the ACLR performance at the cost of introducing more signal distortion.

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