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研究生:陳建甫
研究生(外文):Chen-Fu Chen
論文名稱:在多使用者解碼前送合作式網路系統下聯合中繼選擇與中繼端功率分配以及使用者頻寬分配之演算法
論文名稱(外文):Joint Relay Selection, Bandwidth Allocation and Power Distribution via Genetic Algorithm in Decode-and-Forward Relay Networks
指導教授:方文賢
指導教授(外文):Wen-Hsien Fang
口試委員:方文賢
口試日期:2012-07-20
學位類別:碩士
校院名稱:國立臺灣科技大學
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:2012
畢業學年度:100
語文別:中文
論文頁數:56
中文關鍵詞:基因演算法解碼前送合作式通訊網路中繼端選擇功率分配頻寬分配
外文關鍵詞:Genetic algorithmdecode-and-forward cooperative networksrelay selectionpower distributionbandwidth allocation.
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在無線合作式通訊技術中, 藉由來源端與使用者互相傳遞訊息而形
成空間中的分散式天線陣列, 進而提供的空間分級增益, 此外基於已知各
傳輸路徑的通道狀態, 藉由選擇合適的中繼端來協助傳輸, 並搭配適當的
功率分配, 以及考量在有限的頻譜中, 做有效的分配能夠使系統更容易滿
足無線傳輸容量的需求。
在本論文中, 考量一個多使用者在解碼前送合作式通訊網路的下行傳
輸環境, 基於我們中繼端合作式通訊機制是考量在有限的功率和頻寬資
源下, 對於中繼端選擇與中繼端功率分配以及使用者頻寬分配的最佳化問
題, 我們將此問題之目標函式做推導, 證明此問題是一個凸函數的最佳化
問題, 並且模擬此系統的效能上界。 為了解決此非線性最佳化問題並其降
低系統運行時間, 我們提出以混合式基因演算法來同時實行中繼端選擇與
中繼端功率分配以及使用者頻寬分配來解決, 而提出之混合式基因演算法
之染色體, 將中繼端選擇部分以整數字串基因來表示, 中繼端功率分配以
及使用者頻寬分配部分皆由實數基因所組成, 而整數及實數基因皆有相對
應的混和式交配及突變運算, 以此求取系統最佳解; 而模擬結果顯示我們
所提出的聯合中繼端選擇與中繼端功率分配以及使用者頻寬分配方法之
效能能夠貼近系統上界, 並相較於其他相關文獻的方法能夠有更優異的效
能, 此外亦能夠有效的降低計算複雜度以及縮短其模擬時間。
Cooperative networks are an emerging transmission technique in
which a distributed antenna array can be created and provide the
spatial diversity gains by relaying each other’s messages to the des-
tination. It is well known that the performance of a cooperative
network can be enhanced by appropriate resource allocation based
on the channel state information.
To attain superior performance for the downlink of cooperative
multi-user decode-and-forward (DF) systems, in this thesis we con-
sider to take some crucial issues in the resource allocation, such as
relay selection, bandwidth allocation, and power distribution, into
consideration as a whole. We first determine an upper bound for
the highly optimization problem considered by ignoring some con-
straints. Thereafter, to resolve this nonlinear optimization problem,
we also propose a genetic approach for joint relay subset selection,
bandwidth allocation and power distribution. To accommodate this
joint consideration, each chromosome in the proposed genetic algo-
rithm (GA) is divided into an integer string for relay selection and
two real number strings for bandwidth allocation and power dis-
tribution. In addition, new crossover and mutation operations are employed for this new type of chromosome. Conducted simulations
show that the proposed GA-based approach can attain close per-
formance as the upper bound and outperforms some representative
previous works.
第一章 緒論 1
1.1 引言 . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究動機與目的 . . . . . . . . . . . . . . . . . . . . 3
1.3 內容章節概述 . . . . . . . . . . . . . . . . . . . . . 4
第二章 相關背景回顧 5
2.1 合作式網路通訊系統 . . . . . . . . . . . . . . . . . 5
2.1.1 三端點式合作式解碼前送網路系統 . . . . 7
2.1.2 多使用者合作式解碼前送網路系統 . . . . 7
2.2 中繼端選擇機制 . . . . . . . . . . . . . . . . . . . . 10
2.2.1 最大化通道增益選擇機制 . . . . . . . . . . 10
2.2.2 最接近中繼端選擇機制 . . . . . . . . . . . 11
2.3 凸函數最佳化 . . . . . . . . . . . . . . . . . . . . . 11
2.3.1 凸集合 . . . . . . . . . . . . . . . . . . . . . 12
2.3.2 凸函數 . . . . . . . . . . . . . . . . . . . . . 12
2.3.3 凸函數最佳化問題 . . . . . . . . . . . . . . 13
2.3.4 凸函數的性質 . . . . . . . . . . . . . . . . . 14
2.4 基因演算法. . . . . . . . . . . . . . . . . . . . . . 14
2.5 結語 . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
第三章 在多使用者解碼前送合作式網路系統下聯合中繼端選擇與中繼端功率分配以及使用者頻寬分配之基因演算法 23
3.1 引言 . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 在多使用者解碼前送合作式網路系統下聯合中繼端選擇與中繼端功率分配以及使用者頻寬分配 . 24
3.3 模擬與分析討論 . . . . . . . . . . . . . . . . . . . . 37
3.4 結語 . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
第四章 結論及未來展望 50
4.1 結論 . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.2 未來展望 . . . . . . . . . . . . . . . . . . . . . . . . 51
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