基于盲源信號分離的全雙工通信自干擾消除研究
發(fā)布時間:2018-09-17 07:56
【摘要】:盲源信號分離(BSS)的課題在信號處理研究方面一直是一個熱門話題,它在現(xiàn)實生活中具有非常重要的意義,同時,它對學(xué)者和專家來說也非常具有挑戰(zhàn)性。盲源信號分離是在不知道傳輸信道和源信號的信息,僅僅知道輸入信號的個別信息特征和接收觀測到的混合信號的前提下,由混合信號分離得出源信號。盲源信號分離研究主要針對傳感器的個數(shù)不少于源信號的個數(shù)(m≥n)的超定模型,常采用獨(dú)立成分分析(ICA)算法,它具有非常明顯的分離效果。但是由于現(xiàn)實情況比較復(fù)雜,超定條件在實際中很難滿足,于是,人們開始研究欠定(mn)模型,由于欠定問題的提出相對較晚,對于它的研究有待不斷深入。本文討論了盲源信號分離的幾種模型以及超定、正定和欠定的算法,并進(jìn)行了仿真研究,得出了理想的效果。同時針對欠定問題,在原有稀疏分量分析的基礎(chǔ)上,改進(jìn)了原有算法,使欠定模型的分離效果更加完美,并且給出了估計信號和原有信號的數(shù)值分析對比,能給人更加直觀的感受。第五代通信系統(tǒng)(5G)的主要技術(shù)是全雙工通信,它可以在同時間同頻率上實現(xiàn)收發(fā)無線數(shù)據(jù),解決了頻譜日漸緊張的問題,也大大增加了無線通信的容量。5G全雙工通信系統(tǒng)的實現(xiàn)的難點(diǎn)之一在于數(shù)字域和模擬域?qū)ο到y(tǒng)產(chǎn)生的自干擾信號的抵抗。針對全雙工通信的自干擾問題,本文介紹了現(xiàn)在的幾種解決此問題的方法,并且在此基礎(chǔ)上將盲源信號分離算法應(yīng)用到解決自干擾問題中,提出了快速獨(dú)立成分分析算法的聯(lián)合信道估計自干擾消除方案,將其中的自干擾信號進(jìn)行了有效的分離。
[Abstract]:The subject of blind source signal separation (BSS) is always a hot topic in signal processing. It is of great significance in real life, and it is also very challenging for scholars and experts. Blind source signal separation is to separate the source signal from the mixed signal without knowing the information of the transmission channel and the source signal, but only knowing the individual information characteristics of the input signal and receiving the observed mixed signal. The study of blind source signal separation is mainly focused on the overdetermined model of sensor number (m 鈮,
本文編號:2245229
[Abstract]:The subject of blind source signal separation (BSS) is always a hot topic in signal processing. It is of great significance in real life, and it is also very challenging for scholars and experts. Blind source signal separation is to separate the source signal from the mixed signal without knowing the information of the transmission channel and the source signal, but only knowing the individual information characteristics of the input signal and receiving the observed mixed signal. The study of blind source signal separation is mainly focused on the overdetermined model of sensor number (m 鈮,
本文編號:2245229
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