【摘要】：21世紀(jì)初網(wǎng)絡(luò)編碼理論取得了突破性進(jìn)展,物理層網(wǎng)絡(luò)編碼技術(shù)利用了無(wú)線環(huán)境下電磁波的廣播特性,將中繼節(jié)點(diǎn)也納入編碼的范圍,使其不僅僅只具有存儲(chǔ)轉(zhuǎn)發(fā)功能,從而提高了網(wǎng)絡(luò)吞吐量并可提高系統(tǒng)的魯棒性,其在安全性和功率消耗方面也有一定的性能提升。MIMO技術(shù)通過(guò)在收發(fā)兩端增加天線的數(shù)目形成并行的鏈路提升網(wǎng)絡(luò)容量并能夠通過(guò)分集復(fù)用等技術(shù)提高可靠性。以上兩種技術(shù)的結(jié)合是本文的研究重點(diǎn)。本文對(duì)無(wú)線通信領(lǐng)域一個(gè)典型的應(yīng)用場(chǎng)景——雙向中繼信道模型做了系統(tǒng)的研究,并詳細(xì)介紹了物理層網(wǎng)絡(luò)編碼技術(shù)和映射方案。在闡述該模型的基礎(chǔ)上,將MIMO和PNC技術(shù)結(jié)合應(yīng)用到雙向無(wú)線中繼信道上,相比于單純的單天線網(wǎng)絡(luò),其在吞吐量和可靠性方面都有更好的性能,但同時(shí)更多的天線數(shù)目和更加復(fù)雜的編碼技術(shù)也會(huì)帶來(lái)一系列問(wèn)題,在接收端信號(hào)的檢測(cè)是其中的難點(diǎn),天線數(shù)目越多,信號(hào)之間的干擾就越嚴(yán)重,檢測(cè)時(shí)如何減少其他信號(hào)的干擾和減少錯(cuò)誤傳播現(xiàn)象是設(shè)計(jì)檢測(cè)算法的關(guān)鍵。傳統(tǒng)的MIMO-PNC檢測(cè)算法包括ZF檢測(cè)、MMSE檢測(cè)、SIC檢測(cè)和ML檢測(cè)等,ZF和MMSE檢測(cè)是線性檢測(cè)算法,算法簡(jiǎn)單但性能一般,而ML檢測(cè)雖是最優(yōu)檢測(cè)但復(fù)雜度過(guò)高實(shí)用性較差,第四章在串行干擾消除的思想基礎(chǔ)上提出了一種新的檢測(cè)算法QR-GSIC算法,實(shí)現(xiàn)了在不顯著增加復(fù)雜度的基礎(chǔ)上提升檢測(cè)性能,并通過(guò)Matlab仿真軟件進(jìn)行了性能分析。格基規(guī)約輔助檢測(cè)在進(jìn)行信號(hào)檢測(cè)時(shí)能夠減少信道矩陣的條件數(shù)從而減小噪聲的干擾,將其中的LLL算法與QR-GSIC算法結(jié)合,從抑制噪聲方面提高檢測(cè)性能,并通過(guò)仿真驗(yàn)證了改進(jìn)后的QR-GSIC+LLL算法能夠進(jìn)一步提高QR-GSIC的檢測(cè)性能。本文從MIMO與PNC出發(fā),以雙向無(wú)線中繼信道為平臺(tái),重點(diǎn)研究了MIMO-PNC的適用性,并解決MIMO-PNC在信號(hào)檢測(cè)上的難點(diǎn),對(duì)經(jīng)典的算法做了回顧并提出了一些改進(jìn)算法和思路,并通過(guò)仿真驗(yàn)證了改進(jìn)后算法的優(yōu)良性能。
[Abstract]:At the beginning of the 21st century, network coding theory has made a breakthrough. The physical layer network coding technology takes advantage of the broadcast characteristics of electromagnetic waves in wireless environment and brings the relay nodes into the coding scope, so that it not only has the function of storage and forwarding. Thus, the network throughput is improved and the robustness of the system is improved. MIMO technology enhances network capacity by increasing the number of antennas at both ends of the transmitter and receiver to form parallel links to enhance network capacity and improve reliability through diversity multiplexing. The combination of the above two technologies is the focus of this paper. In this paper, the bidirectional relay channel model, a typical application scene in wireless communication field, is systematically studied, and the physical layer network coding technology and mapping scheme are introduced in detail. Based on this model, the combination of MIMO and PNC technology is applied to two-way wireless relay channel. Compared with the single antenna network, it has better performance in throughput and reliability. But at the same time, more antennas and more complex coding technology will also bring a series of problems, in which the detection of signals at the receiving end is difficult. The more the number of antennas, the more serious the interference between the signals. How to reduce the interference of other signals and reduce the error propagation is the key to design the detection algorithm. Traditional MIMO-PNC detection algorithms include ZF detection, MMSE detection, SIC detection and ML detection. ZF and MMSE detection are linear detection algorithms. In chapter 4, based on the idea of serial interference cancellation, a new detection algorithm, QR-GSIC algorithm, is proposed, which improves the detection performance without significantly increasing the complexity, and analyzes the performance through the Matlab simulation software. In order to reduce the noise interference, the LLL algorithm is combined with the QR-GSIC algorithm to improve the detection performance, which can reduce the condition number of the channel matrix and reduce the noise interference when the signal is detected by the lattice-protocol auxiliary detection, and the algorithm is combined with the QR-GSIC algorithm to improve the detection performance. Simulation results show that the improved QR-GSIC LLL algorithm can further improve the detection performance of QR-GSIC. Based on MIMO and PNC, this paper focuses on the applicability of MIMO-PNC and solves the difficulties in signal detection of MIMO-PNC, and gives a review of the classical algorithms and puts forward some improved algorithms and ideas. The excellent performance of the improved algorithm is verified by simulation.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN919.3

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本文編號(hào)：2286312