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射頻大功率場效應器件的非線性模型及其應用

發(fā)布時間:2018-03-23 23:11

  本文選題:非線性模型 切入點:負載牽引 出處:《寧波大學》2015年碩士論文


【摘要】:隨著無線通信技術的快速發(fā)展,射頻大功率場效應器件的應用日益廣泛。在整個射頻電路設計中,尤其在大信號工作狀態(tài)下場效應器件表現(xiàn)出強非線性,射頻功率器件模型起著非常關鍵的作用,準確而通用模型的應用減少射頻電路設計周期和提高設計效率。效率是衡量射頻功率放大器最關鍵的指標之一,其體現(xiàn)了射頻功放把直流功率轉換為射頻功率的能力。本文采用負載牽引技術把大功率場效應器件的非線性轉化為線性研究;在已有的場效應器件大信號等效電路模型研究的基礎上,對cree公司的Ga N功率器件CGH40010進行了大信號徑向基函數(shù)神經(jīng)網(wǎng)絡建模;同時建立開關等效電路模型并且提取參數(shù),應用于高效開關類功放的仿真設計。具體內(nèi)容如下:1.設計并制作了特征阻抗為50Ω的TRL校準件和含有預匹配(四分之一波長阻抗變換器)和偏置電路的測試夾具。在大信號狀態(tài)下提出了采用負載牽引技術,把大功率場效應器件的非線性轉化為線性研究。負載牽引是在待測器件端口,以精確控制的方式調(diào)諧出已知阻抗,以研究待測器件的最佳性能。2.建立了cree公司Ga N功率器件CGH40010的大信號徑向基函數(shù)神經(jīng)網(wǎng)絡模型。首先分析了小信號等效電路模型中元件參數(shù)的意義,采用直接提取法和優(yōu)化法相結合提取元件參數(shù);然后對非線性漏源電流Id s和非線性較強元件柵漏電容Cg d與柵源電容Cg s,分別建立大信號徑向基函數(shù)神經(jīng)網(wǎng)絡模型;最后通過符號定義器件模型將其導入微波計算機輔助設計軟件中,進行模型的驗證與分析。3.建立了CGH40010等效開關電路模型,并將其應用于高效開關功放的設計中。首先提出了應用于開關功放設計中的功率器件的開關等效電路模型,并將直流數(shù)據(jù)和射頻數(shù)據(jù)相結合,以提取模型中的元件參數(shù);然后采用增量求和調(diào)制器將具有較高峰均比的信號,調(diào)制成只有高低電平的恒包絡信號,且通過濾波器后能夠完全無失真地恢復出原始信號;最后采用建立的開關等效電路模型,設計了高效開關功放并進行仿真與分析。
[Abstract]:With the rapid development of wireless communication technology, RF high-power field effect devices are widely used. In the whole RF circuit design, especially in the large signal working state, the field effect devices exhibit strong nonlinearity. RF power device model plays a very important role. The application of accurate and universal model reduces the design cycle of RF circuit and improves design efficiency. Efficiency is one of the most important indexes to measure RF power amplifier. It reflects the ability of RF power amplifier to convert DC power to RF power. On the basis of the research of large signal equivalent circuit model of field effect devices, the large signal radial basis function neural network (RBFNN) model of CGH40010 of cree Company is built, and the switching equivalent circuit model is established and the parameters are extracted. The main contents are as follows: 1. The TRL calibrator with characteristic impedance of 50 惟 and the test fixture with pre-matching (1/4 wavelength impedance converter) and bias circuit are designed and fabricated. Under the condition of large signal, the technology of load traction is proposed. The nonlinear characteristics of high-power field-effect devices are transformed into linear studies. The load traction is to tune out the known impedance in a precise controlled manner at the device port to be tested. In order to study the optimal performance of the device to be tested, the large signal radial basis function neural network model of cree CGH40010 is established. Firstly, the significance of the component parameters in the small signal equivalent circuit model is analyzed. The direct extraction method and optimization method are used to extract the component parameters, and then the large signal radial basis function neural network models are established for nonlinear leakage current ID s, gate leakage capacitance CG d and gate source capacitance CG s. Finally, the symbolic definition device model is introduced into the microwave CAD software, and the model is verified and analyzed. 3. The CGH40010 equivalent switch circuit model is established. And it is applied to the design of high efficiency switching power amplifier. Firstly, the equivalent circuit model of power device applied in the design of switching power amplifier is proposed, and the DC data and RF data are combined to extract the component parameters of the model. Then, the increment summation modulator is used to modulate the signal with higher peak to average ratio, which is only high and low level constant envelope signal, and the original signal can be recovered completely without distortion after the filter. Finally, an efficient switching power amplifier is designed and simulated by using the switch equivalent circuit model.
【學位授予單位】:寧波大學
【學位級別】:碩士
【學位授予年份】:2015
【分類號】:TN386

【共引文獻】

相關博士學位論文 前2條

1 桑磊;AlGaN/GaN HEMT功率器件建模研究及高效率放大器設計[D];電子科技大學;2013年

2 陳勇波;新型微波晶體管噪聲機理與噪聲模型研究[D];電子科技大學;2014年

相關碩士學位論文 前1條

1 范彩云;HEMT器件的小信號建模[D];華東師范大學;2013年

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本文編號:1655622

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