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研究生:林元弘
研究生(外文):LIN, YUAN-HUNG
論文名稱:應用快速估計模型最佳化 多天線通訊裝置的特定吸收率
論文名稱(外文):Optimization of Specific Absorption Rate Based on a Fast Estimation Model for Multiple-Antenna Transmitters
指導教授:陳晏笙
指導教授(外文):CHEN, YEN-SHENG
口試委員:陳晏笙周瑞宏鄭瑞清李士修
口試委員(外文):CHEN, YEN-SHENGCHOU, JUI-HUNGCHEN, JUI-CHINGLI,SHR-SHIOU
口試日期:2019-01-29
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電子工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:中文
論文頁數:163
中文關鍵詞:特定吸收率數學模型最佳化陣列手持裝置
外文關鍵詞:Specific absorption rateOptimization methodsMathematical modelAntenna arraysMobile communicationMobile antennasTransmitters
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本研究利用前人所提出的特定吸收率快速估計模型,拓展為最佳化的數學式,使多天線陣列在主波束對準目標物之外,還能最小化某觀察面的特定吸收率之峰值。特定吸收率是行動通訊手持裝置的重要參數。在多天線手持裝置中,特定吸收率會受到多天線的饋入電流振幅、相位的影響。天線設計者不僅需使天線主波束對準目標物,還需設法減少特定吸收率的數值。然而,分析特定電流振幅、相位所導致的特定吸收率需反覆進行全波模擬,十分費時。為了減少模擬的次數,D. T. Le等人提出一快速估計模型來計算多天線裝置的特定吸收率。此快速估計模型的特色是僅需操作數組預先規畫的模擬,使其電流相位符合特定矩陣的要求,那麼之後要計算任意相位造成的特定吸收率時,就不需再透過全波模擬重新分析,僅需依照那數組模擬的結果進行運算,就可以快速得到精準的響應。然而,此快速估計模擬尚未考量不同電流振幅的運算,僅能就均勻分佈的電流計算特定吸收率。
本研究拓展了D. T. Le等人研究方法的效力,使此模型能夠分析各種電流振幅、相位的特定吸收率,且模型依然保持快速估計的特徵。我們以全波模擬檢驗提案方法,發現模擬結果與數值分析有良好的一致性。之後,我們利用此模型,以觀察面的最大特定吸收率為目標函數,並以多天線的電流振幅為決策變數,利用列舉法解出最小化特定吸收率的電流分佈。我們以操作於四單元天線進行驗證,使天線陣列的主波束分別對準0˚、± 10˚、± 20˚、…、± 80˚、± 90˚,最小化這些情境的特定吸收率。最佳化結果顯示本方法能有平均15%的改善。最後,本研究實作此四單元天線,量測其二維輻射場型,驗證方法的準確性。

We use a rapid estimating model to calculate specific absorption rate (SAR) proposed by preceding studies to expand into optimized models. The SAR value is an important parameter for mobile handheld communication devices. We direct the primary beam of an antenna array toward the desired direction and minimize the maximum SAR value on an observation plane of a phantom simultaneously. In multi-antenna devices, the SAR value is affected by current amplitude distribution and excitation phases of feed currents. Mobile antennas designers will need to align the main beam of the multi-antenna while it is aiming at a target, as well as attempt to minimize the SAR value.
However, it is very time-consuming to analyze the specific current amplitude distribution and phase angle caused by the SAR value through full-wave simulations. To reduce the number of simulations, Le’s research team proposed a fast estimation model to calculate the SAR value of multi-antenna transmitting devices. The key feature of this fast estimation model is that solely the pre-planned simulations for the array need to be managed and the current phase angles should satisfy the requirements of a specific matrix. Then, after calculating the SAR value caused by any phase angle, there is no need to re-analyze the phase angle through full-wave simulations, and we only need to follow the results of the array simulation to obtain a fast and accurate response. However, the rapid estimation simulation of the reference did not consider the calculation of different current amplitudes, and only the SAR value for a uniform current distribution can be obtained.
Here, we expand the valid range of the cited method, allowing the model applied to the specific absorption rate values of arbitrary current amplitudes and excitation phases, and the model still demonstrates fast estimation. We used the full-wave simulation to verify the proposed method and the simulation results are in agreement with the numerical analysis. This indicates that this model uses the maximum SAR value of the surface as an objective function and uses the current amplitudes of multiple antennas as the decision variables. We use the enumeration method to solve the current distribution that minimizes the specific absorption rate. The four-antenna elements array was validated such that the primary beam of the antenna array is angled at 0˚, ±10˚, ±20˚… ±80˚, ±90˚, respectively, to minimize the maximum SAR value of these situations. The optimization results demonstrate that the method exhibits an average improvement of 19%. Finally, this thesis implements this four-antenna element array, which verified the accuracy of the method by measuring its radiation pattern.

摘要 i
英文摘要 iii
誌謝 v
目錄 vi
圖目錄 viii
表目錄 xvi

第一章 緒論 1
1.1 研究動機 1
1.2 研究現況 6
1.3 研究目的 18
1.4 論文章節大綱 18

第二章 研究方法 20
2.1 特定吸收率理論 22
2.2 提案方法 29

第三章 第一階段:快速估計模型之建立 31
3.1 案例分析之情境介紹 31
3.2 組織液環境 38
3.3 模擬結果 45

第四章 第二階段:以快速估計模型合成饋入權重 70
4.1 數值結果及模擬驗證 70
4.2 實驗驗證 94
4.2.1 單元天線 94
4.2.2 饋入網路 108
4.2.3 四單元天線結合饋入網路 141
4.3 結果及討論 155

第五章 結論 157
5.1 總結 157
5.2 研究限制 158
5.3 未來研究方向 158

參考文獻 160

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