發(fā)布時(shí)間：2018-02-11 08:17

  本文關(guān)鍵詞： 多輸入多輸出 空間調(diào)制 信號(hào)檢測(cè) 檢測(cè)性能 最大似然 格約減　出處：《南京信息工程大學(xué)》2016年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：為了滿(mǎn)足未來(lái)移動(dòng)發(fā)展需求,無(wú)線(xiàn)通信系統(tǒng)一直在追求更高的數(shù)據(jù)傳輸速率,研究的關(guān)鍵挑戰(zhàn)是找到具有潛力的多天線(xiàn)傳輸技術(shù)。針對(duì)現(xiàn)有多輸入多輸出系統(tǒng)(MIMO)發(fā)射天線(xiàn)間的同步與信道間干擾等問(wèn)題,提出了空間調(diào)制技術(shù)(SM)。為了實(shí)現(xiàn)更優(yōu)的多天線(xiàn)傳輸,本文對(duì)空間調(diào)制技術(shù)進(jìn)行了較為深入地研究,主要工作如下：第一,詳細(xì)分析了空間調(diào)制傳統(tǒng)的檢測(cè)算法,包括最大似然檢測(cè)以及分塊排序最小均方誤差(OB-MMSE)檢測(cè)算法。現(xiàn)有的最大似然檢測(cè)算法,由于其計(jì)算復(fù)雜度極高,嚴(yán)重限制了其在實(shí)際中的應(yīng)用,而計(jì)算復(fù)雜度較低的分塊排序最小均方誤差(OB-MMSE)算法在高維發(fā)射天線(xiàn)檢測(cè)性能較差。針對(duì)上面算法的不足,本文在OB-MMSE算法的基礎(chǔ)上提出了兩種新的算法。一種是空間調(diào)制系統(tǒng)格約減輔助檢測(cè)算法(LR-OB-MMSE),該算法解決了OB-MMSE算法在高維度發(fā)射天線(xiàn)情況下性能較差和傳統(tǒng)最大似然檢測(cè)算法復(fù)雜度高的問(wèn)題。另一種是在OB-MMSE基礎(chǔ)上的一種高效計(jì)算集中最大似然檢測(cè)算法,即CECML-OB-MMSE算法。該算法避免了冗余計(jì)算,使計(jì)算提前終止,降低了計(jì)算復(fù)雜度,而且檢測(cè)性能沒(méi)有明顯下降。以上兩種改進(jìn)方案都是運(yùn)用不同算法進(jìn)行了聯(lián)合檢測(cè),能在復(fù)雜度和檢測(cè)性能之間取得良好折中。第二,對(duì)改進(jìn)的算法進(jìn)行仿真研究。首先,對(duì)SM系統(tǒng)收發(fā)天線(xiàn)數(shù)目、檢測(cè)算法,及調(diào)制方式等參數(shù)不同的條件下進(jìn)行仿真,通過(guò)誤比特率和浮點(diǎn)數(shù)曲線(xiàn)分析其性能和計(jì)算復(fù)雜度。其次,在性能和復(fù)雜度方面對(duì)改進(jìn)的方案與傳統(tǒng)檢測(cè)算法進(jìn)行對(duì)比分析。通過(guò)仿真驗(yàn)證本文提出的新的算法合理性與可靠性：LR-OB-MMSE算法在高維發(fā)射天線(xiàn)情況下有效地降低了誤碼率,其檢測(cè)性能優(yōu)于OB-MMSE算法并且趨于最大似然檢測(cè),同時(shí)具有較低的復(fù)雜度；CECML算法在較高信噪比情況下性能沒(méi)有明顯變化,但其復(fù)雜度降低了超過(guò)50%。
[Abstract]:In order to meet the needs of future mobile development, wireless communication systems have been pursuing higher data transmission rates. The key challenge of the research is to find the potential multi-antenna transmission technology. Aiming at the problems of synchronization and inter-channel interference between the transmitting antennas of the existing multiple-input and multi-output systems, a spatial modulation technique is proposed to achieve better multi-antenna transmission. The main work of this paper is as follows: first, the traditional detection algorithm of spatial modulation is analyzed in detail. It includes maximum likelihood detection and block sorting minimum mean square error (OB-MMSE) detection algorithm. Due to its high computational complexity, the existing maximum likelihood detection algorithm severely limits its application in practice. However, the OB-MMSE algorithm, which has low computational complexity, has a poor performance in the detection of high-dimensional transmit antennas. This paper proposes two new algorithms based on the OB-MMSE algorithm. One is the LR-OB-MMSE algorithm, which solves the problem of poor performance of the OB-MMSE algorithm and the traditional maximum likelihood algorithm in the case of high-dimensional transmit antennas. The other is an efficient algorithm based on OB-MMSE. That is, CECML-OB-MMSE algorithm, which avoids redundant computation, reduces computational complexity, reduces computational complexity, and does not significantly reduce detection performance. Both of the above two improved schemes use different algorithms to perform joint detection. It can achieve a good compromise between complexity and detection performance. Secondly, the improved algorithm is simulated. First, the number of antenna, detection algorithm, modulation and other parameters of SM system are simulated. The performance and computational complexity are analyzed by bit error rate and floating-point curve. Secondly, The performance and complexity of the improved algorithm and the traditional detection algorithm are compared and analyzed. The simulation results show that the proposed new algorithm is reasonable and reliable, which can effectively reduce the bit error rate (BER) in the case of high-dimensional transmitting antenna. Its detection performance is superior to that of OB-MMSE algorithm and tends to maximum likelihood detection. At the same time, the performance of OB-MMSE algorithm with lower complexity does not change obviously in the case of higher SNR, but its complexity is reduced by more than 50%.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TN929.5;TN919.3
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本文編號(hào)：1502597