本文關(guān)鍵詞： Massive MIMO 置信度傳播 低復(fù)雜度 禁忌搜索　出處：《安徽大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：多輸入多輸出(MIMO)檢測技術(shù)發(fā)展到今天已經(jīng)相當(dāng)成熟了。Massive MIMO技術(shù)作為傳統(tǒng) MIMO 技術(shù)的擴展已經(jīng)成為 5G(the 5th Generation mobile communication technology)的核心技術(shù)之一,其具有更高的頻譜效率和信道容量。然而,在Massive MIMO系統(tǒng)中存在著很多問題,由于眾多的天線數(shù)目,接收信號復(fù)雜,高維度的信道矩陣等,對接收端的信號檢測算法提出了更高的要求,希望以較低的復(fù)雜度實現(xiàn)良好的性能�；谶@種背景,本文重點對適用于Massive MIMO信號檢測的主動禁忌搜索(Reactive Tabu Search,RTS)算法進(jìn)行了詳細(xì)介紹并在此基礎(chǔ)上進(jìn)一步深入研究,介紹了兩種改進(jìn)方法。RTS算法作為Massive MIMO中比較優(yōu)秀的檢測算法,近年來引起了學(xué)者們的高度關(guān)注。本文主要就如何進(jìn)一步提高RTS算法的性能以及改善RTS算法在高階調(diào)制方式下性能表現(xiàn)不佳的問題進(jìn)行了研究。本文給出了兩種基于RTS的改進(jìn)方法:隨機重啟主動禁忌搜索(Random Condition Restar-Reactive Tabu Search,RCR-RTS)算法和 RTS-BP(Reactive Tabu search-BeliefPropagation)聯(lián)合檢測算法,并對它們進(jìn)行了仿真分析。本文首先介紹了 MIMO系統(tǒng)及其信號檢測技術(shù)的研究背景和面臨的現(xiàn)狀,并簡要的概述了 MIMO系統(tǒng)模型和幾種常見的信號檢測算法。再詳細(xì)闡述了適用于Massive MIMO系統(tǒng)下的RTS算法的基本原理和實現(xiàn)流程圖,分析了該算法在Massive MIMO信號檢測中的優(yōu)勢,并在不同QAM(Quadrature Amplitude Modulation)調(diào)制下對該檢測算法進(jìn)行了仿真分析。然后介紹了一種基于RTS的改進(jìn)方法,即RCR-RTS檢測算法,詳細(xì)論述了對RTS算法的改進(jìn),給出了算法的詳細(xì)流程并進(jìn)行了仿真分析。該改進(jìn)方法提高了檢測性能,同時也改善了傳統(tǒng)RTS算法在高階調(diào)制系統(tǒng)中性能不佳的問題。接著,對標(biāo)準(zhǔn)的BP-GAI(Belief Propagation-Gauss Approximation Interference)算法進(jìn)行基本分析,將 RTS 算法與BP算法相結(jié)合,介紹了另一種基于RTS的改進(jìn)方法,即RTS-BP聯(lián)合檢測算法,并仿真驗證了該改進(jìn)算法性能較RTS算法得到了提升,也能在一定程度上改善RTS算法在高階調(diào)制系統(tǒng)中性能不佳的情況。最后,對給出的RCR-RTS和RTS-BP這兩種檢測算法做了性能和復(fù)雜度的分析比較,并得出結(jié)論,本文介紹的RCR-RTS和RTS-BP檢測算法,是從兩個完全不同的角度對RTS算法的改進(jìn)。這兩種基于RTS的檢測算法都有各自的優(yōu)點,在Massive MIMO中的性能表現(xiàn)良好,都是非常適用于Massive MIMO系統(tǒng)中的信號檢測算法。本文主要以具有低復(fù)雜度高性能的主動禁忌搜索(RTS)算法為重點,并在此基礎(chǔ)上介紹了兩種改進(jìn)方法,在配備多天線的Massive MIMO系統(tǒng)信號檢測中具有良好的性能表現(xiàn),為Massive MIMO信號檢測問題帶來了一些新鮮的方法及思路。
[Abstract]:Multiple-Input-Multiple-Output (Mimo) Detection Technology has been developed to a considerable maturity today. Massive MIMO technology as an extension of traditional MIMO technology has become a 5G (. One of the core technologies of the 5th Generation mobile communication. However, there are many problems in Massive MIMO systems, such as the number of antennas, the complexity of received signals, the high dimensional channel matrix and so on. In order to achieve good performance with low complexity, the signal detection algorithm of the receiver is required higher. Based on this background. This paper focuses on active Tabu Search, which is suitable for Massive MIMO signal detection. RTS) algorithm is introduced in detail and further studied on this basis. Two improved methods. RTS algorithm is introduced as a better detection algorithm in Massive MIMO. In recent years, scholars have paid close attention to it. This paper mainly studies how to further improve the performance of RTS algorithm and how to improve the performance of RTS algorithm under high-order modulation. Two improved methods based on RTS are presented:. Random restart active Tabu search (. Random Condition Restar-Reactive Tabu Search. The RCR-RTS) algorithm and the RTS-BP(Reactive Tabu search-BeliefPropagation joint detection algorithm. At first, this paper introduces the research background and current situation of MIMO system and its signal detection technology. The model of MIMO system and several common signal detection algorithms are briefly summarized, and the application of Massive is described in detail. The basic principle and implementation flow chart of RTS algorithm in MIMO system. The advantages of this algorithm in Massive MIMO signal detection are analyzed. And in different QAM(Quadrature Amplitude Modulations). The algorithm is simulated and analyzed under modulation. Then an improved method based on RTS is introduced. That is, the RCR-RTS detection algorithm, the improvement of the RTS algorithm is discussed in detail, the detailed flow of the algorithm is given and the simulation analysis is carried out. The improved method improves the detection performance. At the same time, it also improves the performance of traditional RTS algorithm in high-order modulation system. Standard BP-GAI(Belief Propagation-Gauss Approximation Conference). Algorithm for basic analysis. Combining RTS algorithm with BP algorithm, another improved method based on RTS, RTS-BP joint detection algorithm, is introduced. The simulation results show that the improved algorithm can improve the performance of RTS algorithm and improve the performance of RTS algorithm in high order modulation system to some extent. Finally. The performance and complexity of the two detection algorithms, RCR-RTS and RTS-BP, are analyzed and compared, and the conclusion is drawn that the RCR-RTS and RTS-BP detection algorithms are introduced in this paper. It is the improvement of RTS algorithm from two completely different angles. These two detection algorithms based on RTS have their own advantages, and the performance in Massive MIMO is good. These algorithms are very suitable for signal detection in Massive MIMO system. This paper focuses on the active Tabu search algorithm with low complexity and high performance. On this basis, two improved methods are introduced, which have good performance in signal detection of Massive MIMO system with multiple antennas. It brings some new methods and ideas for Massive MIMO signal detection.
【學(xué)位授予單位】：安徽大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN929.5

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