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研究生:張博凱
研究生(外文):Bo-Kai Chang
論文名稱:粒子群與禁忌搜尋演算法之整合及其於上行正交分頻多重存取系統載波頻率偏移估計之應用
論文名稱(外文):Mixing Particle Swarm Optimization and Tabu Search Algorithm and Its Application to Estimation of Carrier Frequency Offsets for Uplink OFDMA System
指導教授:譚旦旭譚旦旭引用關係
指導教授(外文):Tan-Hsu Tan
口試委員:黃正光黃永發簡福榮
口試委員(外文):Jeng-Kuang HwangYung-Fa HuangFu-Rong Jean
口試日期:2013-07-25
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系所
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:2013
畢業學年度:101
語文別:中文
論文頁數:70
中文關鍵詞:粒子群演算法禁忌搜尋演算法正交分頻多重存取載波頻率偏移
外文關鍵詞:Particle Swarm Optimization (PSO)Tabu Search (TS)Orthogonal Frequency Division Multiple Access (OFDMA)Carrier Frequency Offset (CFO)
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禁忌搜尋(Tabu Search, TS)與粒子群演算法(Particle Swarm Optimization, PSO)均屬演化式演算法(Evolutionary Algorithm),且被廣泛應用在許多最佳化問題中,其中TS的效能相當依賴初始解,因此本研究利用PSO提供TS合適的初始解。另外,待解變數的增加會導致候選解(Candidate Solutions)的多樣性(Diversity)不足而讓求解的效果銳減,故本研究進一步加上突變(Mutation)機制,以增加族群個體多樣性,同時提升區域搜尋能力。
此一混合型演算法經一系列測試函數驗證,其效果優於其他方法。接著我們將此一演算法應用於估計上行正交分頻多重存取(Orthogonal Frequency Division Multiple Access, OFDMA)系統之載波頻率偏移(Carrier Frequency Offsets, CFOs)。模擬結果顯示,與整合田口運算及突變之粒子群演算法(Taguchi-based Mutation PSO, THM-PSO)相較,本研究提出的方法可以估計出較精確的CFOs。

The Tabu search (TS) and particle swarm optimization (PSO) algorithm are developed based on evolutionary computation, which have been extensively applied in many optimization problems. Since PSO and TS are relatively more capable for global exploration and local search, respectively, than many other heuristic algorithms, a new approach combining PSO and TS is proposed in this study. Because of the performance of TS is highly dependent on the initial solution, this study employs PSO to provide suitable initial solution for TS. Furthermore, the lack of diversity of candidate solution can easily trap the final solution into local optimum as the dimension of solution space increases. Hence, mutation operation is further introduced to increase the diversity of candidate solution for enhancement of local search capability of the proposed scheme.
The proposed approach has been verified based on a number of benchmark functions, which demonstrates the best performance as compared to other schemes. This approach is then applied to estimate the carrier frequency offsets (CFOs) encountered in the uplink orthogonal frequency division multiple access (OFDMA) system. Experimental results indicate that the proposed approach is superior to Taguchi-based Mutation PSO (THM-PSO) in terms of mean square error, symbol error rate, and computational burden per generation.

目 錄
中文摘要 i
英文摘要 ii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1研究動機與目的 1
1.2研究方法 3
1.3論文架構 4
第二章 最佳化演算法 5
2.1 粒子群演算法 5
2.2.1 簡介 5
2.2.2 粒子群演算法之原理 6
2.2.3 粒子群演算法之發展 6
2.2.4 多樣性測量 7
2.2.5 粒子群演算法之流程 8
2.2 應用突變之線性權重粒子群演算法 10
2.3 禁忌搜尋演算法 13
2.3.1 簡介 13
2.3.2 禁忌搜尋演算法之原理 13
2.3.3 禁忌搜尋演算法之流程 16
2.4 整合突變機制之粒子群與禁忌搜尋演算法 17
2.5 函數測試 20
第三章 正交分頻多工系統 22
3.1 簡介 22
3.2 正交分頻多工原理 22
3.2.1 多載波調變 22
3.2.2 正交分頻多工系統之運作 23
3.3 正交分頻多工架構 25
3.4 正交分頻多工在頻率選擇性衰減通道之效能 27
3.5 保護區間與循環字首 28
3.6 正交分頻多重存取 32
3.7 同步問題 33
3.8 正交分頻多工之優缺點 34
第四章 整合突變機制之粒子群與禁忌搜尋之載波頻率偏移估計 35
4.1 訊號模型 35
4.1.1 領航訊號設計 36
4.1.2 接收訊號 36
4.1.3 對數概似函數 37
4.2 模擬結果 39
4.2.1 相關參數之效能影響 39
4.2.2 各種演算法之均方誤差 43
4.2.3 各種演算法之符元錯誤率 49
4.2.4 收斂特性與運算時間比較 54
4.2.5 綜合討論 56
第五章 結論 59
參考文獻 60
附錄A 測試函數 65
附錄B 縮寫中英對照 68

表目錄
表2.1 測試函數 20
表2.2 不同演算法於不同函數之誤差 21
表4.1 子載波分配(K=4,N=2048,∆=32 ) 36
表4.2 Mc之設定 39
表4.3 不同Mc值對應之收歛速度與MSE效能 41
表4.4 Rc之設定 41
表4.5 不同Rc值對應之收歛速度與MSE效能 43
表4.6 模擬環境相關設定 43
表4.7 達成特定MSE值所需之SNR與增益(K=4) 46
表4.8 達成特定MSE值所需之SNR與增益(K=8) 47
表4.9 達成特定MSE值所需之SNR與增益(K=16) 48
表4.10 各種SNR下之SER與改善幅度(K=4) 51
表4.11 各種SNR下之SER與改善幅度(K=8) 52
表4.12 各種SNR下之SER與改善幅度(K=16) 53
表4.13 THM-PSO與MPSO-TS於不同用戶數下所需之MSE收斂代數 54
表4.14 THM-PSO與MPSO-TS於不同用戶數下所需之CPU運算時間 55
表4.15 THM-PSO與MPSO-TS於不同用戶數下每次迭代所需時間 55
表4.16 表4.7至4.9之摘要 57
表4.17 表4.10至4.12之摘要 58

圖目錄
圖2.1 PSO演算法之流程圖 9
圖2.2 突變機制 10
圖2.3 LPSO-Mut演算法之流程圖 12
圖2.4 Tabu Search演算法之示意圖 14
圖2.5 Tabu Search演算法之流程圖 17
圖2.6 MPSO-TS演算法之流程圖 19
圖3.1 單載波調變示意圖 23
圖3.2 多載波調變示意圖 23
圖3.3 FDM與OFDM的頻譜 24
圖3.4 OFDM架構 26
圖3.5 SCM與MCM在頻率選擇性通道之效能 27
圖3.6 保護區間與延遲擴展 28
圖3.7 具CP之OFDM符元示意圖 28
圖3.8 雙路徑通道脈衝響應 28
圖3.9 傳送訊號 (a)未加GI, (b)加入GI, (c)加入CP 30
圖3.10 接收訊號 (a)未加GI, (b)加入GI, (c)加入CP 31
圖3.11 子載波分配方式(K=4,N=16) (a) SCAS, (b) ICAS, (c) GCAS 32
圖3.12 CFO之示意圖 33
圖4.1 上行OFDMA系統 35
圖4.2 MPSO-TS對應Mc之MSE效能 40
圖4.3 MPSO-TS對應Mc之多樣性變化曲線 40
圖4.4 MPSO-TS對應Rc之MSE效能 42
圖4.5 MPSO-TS對應Rc之多樣性變化曲線 42
圖4.6 各種演算法之MSE效能(K=4) 46
圖4.7 各種演算法之MSE效能(K=8) 47
圖4.8 各種演算法之MSE效能(K=16) 48
圖4.9 各種演算法所估計之SER(K=4) 51
圖4.10 各種演算法所估計之SER(K=8) 52
圖4.11 各種演算法所估計之SER(K=16) 53
圖4.12 THM-PSO與MPSO-TS於不同用戶數下之MSE收斂特性 54
圖4.13 THM-PSO與MPSO-TS於不同用戶數下每次迭代所需時間折線圖 56

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