臺灣博碩士論文加值系統

在毫米波(millimeter wave, mmWave)大規模多重輸入多重輸出(massive multiple-input multiple-output, massive MIMO)通訊系統中，於系統傳送端使用混合式類比/數位預編碼架構(hybrid analog/digital precoding)及低解析度(low-resolution)的數位類比轉換器(digital to analog converter, DAC)，是一種有效降低系統功率消耗(power consumption)的方法。本文主要研究具有混合式類比/數位預編碼設計之毫米波大規模多重輸入多重輸出通訊系統下的DAC動態式解析度演算法。由於毫米波系統下波長較短，可以在相同面積下擺放更多的天線陣列以提升傳輸效能，但配置大型的天線陣列使得硬體成本及功率消耗大幅提升，為了在傳輸效能與功率消耗之間取得一個平衡點，本文以最大化能量效率(energy efficiency, EE)為準則提出了四種DAC動態式解析度(dynamic-resolution)的演算法，分別是窮舉法(exhaustive)、精簡版窮舉法(exhaustive-lite)、貪婪法(greedy)、以及二分法(bisection)，並且分析四種演算法對於毫米波MIMO通訊系統效能的影響。最後由電腦模擬結果得出，具有動態式解析度的DAC架構，除了系統總合傳輸率(achievable sum-rate, ASR)可以逼近全解析度(full-resolution)的DAC架構外，更可以降低系統的功率消耗，使其能量效率提升。

A hybrid precoding transmitter with low-resolution digital-to-analog converters (DACs) is a promising low-power approach for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. In this paper, we concentrate on the dynamic-resolution DAC algorithms for mmWave massive MIMO systems with hybrid analog/digital precoding design. At mmWave frequencies, due to the small wavelength of mmWave signals, the large antenna arrays could be deployed. This allows signal transmission with ultra high data rates thanks to large bandwidths available at the mmWave frequency band. However, large antenna arrays be deployed will cause high hardware cost and power consumption. To derive a tradeoff between power consumption and spectral efficiency of massive MIMO systems at mmWave frequencies, three novel dynamic-resolution DAC algorithms, namely, the exhaustive, exhaustive-lite, and greedy schemes, are developed based on the maximization of energy efficiency (EE). Finally, simulation results demonstrate that a dynamic-resolution DAC architecture is capable of providing an achievable sum-rate (ASR) approaching to the full-resolution DAC system and a superior EE performance.

目錄
章節 頁碼
致謝 i
中文摘要 ii
英文摘要 iii
目錄 iv
圖目錄 vi
表目錄 viii
第一章 簡介 1
1.1 前言 1
1.2 研究動機 3
1.3 論文架構 4
第二章 毫米波通道系統之混合式預編碼器 5
2.1 系統模型 5
2.2 毫米波通道模型 9
2.3 功率消耗 11
2.4 能量效率 12
2.5 問題公式化 13
第三章 混合式預編碼器設計 16
3.1 天線連接架構介紹 16
3.2 全數位預編碼器設計 18
3.3 全連接預編碼器設計 19
3.4 子連接預編碼器設計 21
3.5 動態子連接預編碼器設計 23
3.5.1 動態子連接簡介 23
3.5.2 組化相鄰相關演算法 24
3.5.3 Gram-Schmidt (GS)正交法演算法 26
3.5.4 動態預定義集合演算法 28
第四章 DAC動態解析演算法設計 30
4.1 動態解析DAC簡介 30
4.2 窮舉法 31
4.3 精簡版窮舉法 32
4.4 貪婪法 34
4.5 二分法 36
第五章 電腦模擬與分析 37
5.1 電腦模擬環境參數設定 37
5.2 模擬結果分析 38
5.3 運算複雜度分析 53
第六章 結論與未來展望 55
參考文獻 56

圖目錄
圖 頁碼
2.1 毫米波massive MIMO通訊系統之混合式預編碼 5
3.1 (a) 全連接(fully-connected)天線架構 16
3.1 (b) 部分連接(partially connected)天線架構 16
3.1 (c) 動態連接(dynamically connected)天線架構 16
3.2 組化相鄰相關演算法示意圖 24
3.3 (a) 在均勻方形平面陣列之水平(horizontal)式分配的子連接天線架構 28
3.3 (b) 在均勻方形平面陣列之垂直(vertical)式分配的子連接天線架構 28
3.3 (c) 在均勻方形平面陣列之方型(squared)式分配的子連接天線架構 28
4.1 二分法示意圖 36
5.1 (a) 組化相鄰相關法在均勻線性天線陣列下之動態解析度系統能量效率比 較圖 39
5.1 (b) 組化相鄰相關法在均勻線性天線陣列下之動態解析度系統總和傳輸 率比較圖 39
5.2 (a) Gram-Schmidt正交法在均勻線性天線陣列下之動態解析度系統能 量效 率比較圖 41
5.2 (b) Gram-Schmidt正交法在均勻線性天線陣列下之動態解析度系統 總 和傳輸率比較圖 41
5.3 (a) Gram-Schmidt正交法與組化相鄰相關法在均勻線性天線陣列下之 動態 解析度系統能量效率比較圖 43
5.3 (b) Gram-Schmidt正交法與組化相鄰相關法在均勻線性天線陣列下之 動態 解析度系統總和傳輸率比較圖 43
5.4 (a) 動態預定義集合法在均勻方型平面天線陣列下之動態解析度系統 能量 效率比較圖 46
5.4 (b) 動態預定義集合法在均勻方型平面天線陣列下之動態解析度系統總 和傳輸率比較圖 46
(c) 動態預定義集合法之預定義(pre-defined set)集合的比例圖 47
5.5 (a) 資料串流量對於不同動態子連接架構的能量效率影響圖 49
5.5 (b) 資料串流量對於不同動態子連接架構的總和傳輸率影響圖 49
5.6 (a) 組化相鄰相關法、Gram-Schmidt正交法與動態預定義集合法在均 勻方型平面天線陣列下之動態解析度系統能量效率比較圖 52
5.6 (b) 組化相鄰相關法、Gram-Schmidt正交法與動態預定義集合法在均 勻方型平面天線陣列下之動態解析度系統總和傳輸率比較圖 52

表目錄
表 頁碼
2.1 不同解析度b下的 值 6
2.2 傳送端元件功率消耗表 11
3.1 組化相鄰相關演算法 25
4.1 精簡版窮舉法 33
4.2 貪婪法 35
5.1 動態子連接架構與DAC動態解析演算法之複雜度分析表 53

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