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研究生: 黃昭瑋
Huang, Chao-Wei
論文名稱: Two-Way Training Design for Discriminatory Channel Estimation in Wireless MIMO Systems
指導教授: 洪樂文
Hong, Yao-Win Peter
口試委員: 蔡育仁
葉丙成
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 通訊工程研究所
Communications Engineering
論文出版年: 2011
畢業學年度: 99
語文別: 英文
中文關鍵詞: 人工雜訊通道估計
外文關鍵詞: artificial noise, channel estimation
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  • 本論文針對多輸入多輸出系統(MIMO)提出可用以區分合法接收者和非法接收者間通道估計效能的雙向訓練訊號設計。本研究延伸自過去已提出的差異性通道估計技術(discriminatory channel estimation)
    。差異性通道估計技術旨在最小化合法接收者的通道估計錯誤並同時將非法接收者的通道估計錯誤維持在某個標準以上。如果訓練訊號只能單從傳送者發送,合法接收者和非法接收者間的效能差異則將有所限制。這是因為傳送者所發出的訓練訊號會同時幫助兩方接收者執行其通道估計。本論文所提出的雙向訓練方法允許傳送者和合法接收者都發送訓練訊號。在此情況下,由合法接收者發送的訓練訊號將幫助傳送者得到關於傳送者至合法接收者間的通道資訊,但卻無助於非法接收者去估計傳送者至非法接收者間的通道。當傳送者估得它到合法接受者間的通道後,其可在下一次的訓練訊號上加上人工雜訊(artificial noise)以擾亂非法接收者的通道估計。此人工雜訊應散佈於傳送者到合法接收者間通道估計的零空間上以減少對合法接收者的干擾。基於此概念,我們分別就對等通道(reciprocal channel)和非對等通道(non-reciprocal channel)提出各自的雙向差異性通道估計技術。在總和與個別能量限制下,我們求得訓練訊號和人工雜訊間的最佳能量分配,並藉由數值模擬結果驗證所提出雙向差異性通道估計的效能。


    Thisworkexaminestheuseoftwo-waytraininginmultiple-inputmultiple-output(MIMO)wirelesssystemstodiscriminatethechannelestimationperformancesbetweenalegitimatereceiver(LR)andanunauthorizedreceiver(UR).Thisthesisextendsuponthepreviouslyproposeddiscriminatorychannelestimation(DCE)schemethatallowsonlythetransmittertosendtrainingsignals.ThegoalofDCEistominimizethechannelestimationerroratLRwhilerequiringthechannelestimationerroratURtoremainbeyondacertainlevel.Ifthetrainingsignalissentonlybythetransmitter,theperformancediscriminationbetweenLRandURwillbelimitedsincethetrainingsignalshelpbothreceiversperformestimatesoftheirdownlinkchannels.Inthiswork,weconsiderinsteadthetwo-waytrainingmethod-ologythatallowsboththetransmitterandLRtosendtrainingsignals.Inthiscase,thetrainingsignalsentbyLRhelpsthetransmitterobtainknowledgeofthetransmitter-to-LRchannel,butdoesnothelpURestimateitsdownlinkchannel(i.e.,thetransmitter-to-URchannel).Withtransmitterknowledgeoftheestimatedtransmitter-to-LRchannel,artificialnoise(AN)canthenbeembeddedinthenullspaceofthetransmitter-to-LRchanneltodisruptUR’schannelestimationwithoutseverelydegradingthechannelestimationatLR.Basedontheseideas,two-wayDCEtrainingschemesaredevelopedforbothreciprocalandnon-reciprocalchannels.TheoptimalpowerallocationbetweentrainingandANsignalsisdevisedunderbothaverageandindividualpowerconstraints.Numericalresultsareprovidedtodemonstratetheefficacyoftheproposedtwo-wayDCEtrainingschemes.

    Abstract i Contents ii 1 Introduction . . . . . . . . . .1 2 SystemModel . . . . . . . . . . 4 3 Two-Way Training Strategy for Reciprocal Channels 7 4 Optimal Power Allocation for DCE in Reciprocal Channels 9 4.1 Channel Estimation Performance at Transmitter . . . . . . . . . . . . . . . . 9 4.2 Channel Estimation Performance at LR and UR . . . . . . . . . . . . . . . . 10 4.3 Optimal Power Allocation between Training and AN Signals . . . . . . . . . 11 5 Two-Way Training Strategy for Non-reciprocal Channels 14 6 Optimal Power Allocation for DCE in Nonreciprocal Channels 18 6.1 Channel Estimation Performance at Transmitter . . . . . . . . . . . . . . . . 18 6.2 Channel Estimation Performance at LR and UR . . . . . . . . . . . . . . . . 20 6.3 Optimal Power Allocation between Training and AN Signals . . . . . . . . . 24 7 Numerical Results and Discussions 25 8 Conclusion 32 9 Appendix 33 9.1 Proof of Proposition I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 9.2 Monomial Approximation and Condensation Method for the Problem in (6.33) 36

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