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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/49514

Title: Block RLS演算法於MIMO STBC CP-OFDM系統之適應性等化器研究
Authors: Hung, Chun-Hao
黃俊皓
Contributors: NTOU:Department of Communications Navigation and Control Engineering
國立臺灣海洋大學:通訊與導航工程學系
Keywords: 多輸入多輸出;多使用者;正交分頻多工調變;空時區塊碼;最小均方差等化器;Wiener等化器;Block Recursive Least-Squares(BRLS);盲蔽式等化器
Multiple-input Multiple-output(MIMO);Multi-user,Orthogonal Frequency Division Modulation(OFDM);Space-Time Block Code(STBC);Least Mean Square(LMS) equalizer;Wiener equalizer;Block Recursive Least-Squares(BRLS);Blind equalizer
Date: 2017
Issue Date: 2018-08-22T07:02:27Z
Abstract: 第四代行動通訊系統以正交分頻多工調變(Orthogonal Frequency Division Modulation, OFDM)技術為主要技術並結合多輸入多輸出(Multiple Input Multiple Output, MIMO)與空時區塊碼(Space-Time Block Coding, STBC)搭配循環字首(Cyclic Prefix,CP)已成為寬頻行動通訊的標準技術之一。近年來通訊系統為達到更高傳輸效率,因此多使用者多輸入多輸出系統技術(Mutiuser-MIMO)也亦趨成熟,故本論文針對多使用者MIMO STBC CP-OFDM無線傳輸系統進行適應性等化器以及頻率等化器設計。 本研究首先利用最小平方差(Least Square Error, LSE)和最小均方誤差(Least Mean Square, LMS)兩種方法並結合正向與反向接收資料之方式,於頻域上設計LSE等化器、正向Wiener等化器以及正反向Wiener等化器。接著考慮多使用者於實際通道環境中,因通道隨時間改變之特性,以Block RLS(Block Recursive Least Square)演算法更新權重矩陣設計適應性等化器,並將BRLS結合正向接收訊號和正反向接收訊號,提出正向BRLS(Forward-Only Block Recursive Least Square,FO-BRLS)適應性等化器與正反BRLS(Forward-Backward Block Recursive Least Square,FB-BRLS)適應性等化器。 最後,為了提高通道容量使用效率,在未知傳送訊號條件下加入決策裝置以完成等化器之權重矩陣更新,並同時使用正向資料與正反向資料提出決策導向之正向盲蔽式等化器和決策導向之正反向盲蔽式等化器設計。 模擬結果顯示本研究提出之FB-BRLS適應性等化器在收斂速度以及還原訊號能力皆比FO-BRLS適應性等化器以及Wiener等化器更優。而在時變環境下,研究所提FB-BRLS和FO-BRLS適應性等化器比Wiener等化器能達到更即時訊號解調的目的。
The combination of MIMO, STBC, CP and OFDM techniques, called the MIMO STBC CP-OFDM system, has becomes one of standards in the fourth-generation (4G) mobile wideband communication.Communication systems in recent years to achieve higher transfer efficiency and multiuser multiple input multiple output technique (Mutiuser-MIMO) has also matured, this thesis will design the equalizer in frequency domains and adaptive equalizer in multiuser MIMO STBC CP-OFDM wireless transmission systems . In this research is using Least Square Error (LSE) and Least Mean Square (LMS) two methods and combining the forward and backward sample data, to designs the LSE equalizer, Wiener equalizer ,and forward-backward Wiener equalizer in the frequency domains.Then considered the multi-users in the real channel environment, characteristics of the channel changed over time , by Block Recursive Least Square (BRLS) the calculating method renewal weight matrix design adaptive equalizer, and combine the forward receive signal and reverse receive signal, are proposing Forward-Only Block Recursive Least Square (FO-BRLS) adaptive equalizer and Forward-Backward Block Recursive Least Square (FB-BRLS) adaptive equalizer. Finally, in order to enhance the efficiency of channel capacity using, joins the decision device under the unknown transmission signal condition to renew the matrix of weight in equalizer, and combines the forward and backward sample data to propose DD-FOBRLS blind equalizer and DD-FBBRLS blind equalizer. The simulation result showed this research proposed the FB-BRLS adaptive equalizer all is more superior than the FO-BRLS adaptive equalizer and the Wiener equalizer in the convergence rate as well as return to original state signal ability. But under the time-variable environment, FB-BRLS and the FO-BRLS adaptive equalizer can achieve the immediate signal demodulation compared to the Wiener equalizer .
URI: http://ethesys.lib.ntou.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=G0010267021.id
http://ntour.ntou.edu.tw:8080/ir/handle/987654321/49514
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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