【摘要】：分布式MIMO(distributed multiple-input multiple-output,D-MIMO)是目前探索第五代移動通信(the fifth generation mobile communication,5G)中的關(guān)鍵技術(shù)之一,具有高容量、高頻譜利用率、低功耗、更好的覆蓋、開放式的結(jié)構(gòu)等優(yōu)點。時延估計一直是通信等領(lǐng)域研究的熱點之一,直接決定著D-MIMO天線系統(tǒng)整體性能的好壞。信號檢測、信道均衡、解調(diào)等信號處理操作都依賴于與時延估計密切相關(guān)的定時同步和信道估計。信道環(huán)境通常是多徑的,目前主流的基于前導(dǎo)的幀同步方法估計的是第一徑為主徑且功率較大情況下的時延。而信道估計中沖激響應(yīng)的位置即為估計的多徑相對時延。因此,本文將從多徑時延估計和幀同步兩個方面探究分布式MIMO天線系統(tǒng)的時延估計。分布式壓縮感知(Distributed Compressed Sensing,DCS)是壓縮感知的擴展,針對多個信號的聯(lián)合稀疏性差異,主要有三種聯(lián)合稀疏模型及其重構(gòu)算法,能夠利用較少的觀測數(shù)實現(xiàn)多個信號的聯(lián)合重構(gòu)估計,已經(jīng)被很好地應(yīng)用在通信系統(tǒng)多個稀疏信道的聯(lián)合估計中。ADMM(Alternating Direction Method of Multipliers)是一種很受歡迎的分布式并行計算的優(yōu)化求解方法,能夠在每次迭代都達到近似最優(yōu)解且計算速度快。對于分布式MIMO天線系統(tǒng)中,多徑時延估計的精度不高、計算復(fù)雜度較大、分辨力不夠等問題,結(jié)合多徑信道的相關(guān)性大小和稀疏性,本文提出了基于ADMM的DCS多徑時延估計方法,包括估計模型的建立、目標(biāo)函數(shù)的確定以及算法求解等步驟。通過仿真實驗表明所提的方法不僅具有較好的時延估計性能,而且提高了分辨力,節(jié)省了測量數(shù)目從而減小了計算復(fù)雜度。針對傳統(tǒng)分布式MIMO天線系統(tǒng)估計第一徑到達時延的幀同步算法中,一般采用遍歷搜索的方法確定正確同步索引點,其存在計算復(fù)雜度和計算量較大的問題。而黃金分割法是求取一維極小化問題的近似最優(yōu)策略,且具有計算復(fù)雜度低的特點。本文從同步度量函數(shù)曲線的幾何特征出發(fā),針對定時同步估計經(jīng)典算法遍歷搜索計算量大的問題,提出一種新穎的基于黃金分割法優(yōu)化的定時同步算法,以其中的幀同步及在分布式MIMO系統(tǒng)的應(yīng)用為例給出了算法流程和復(fù)雜度分析。通過仿真實驗,驗證了所提方法在大幅降低復(fù)雜度的情況下,仍然保持了與傳統(tǒng)算法相當(dāng)?shù)男阅堋?br/>[Abstract]:Distributed multiple-output D-MIMO (D-MIMO) is one of the key technologies in exploring the (the fifth generation mobile communication 5G of the fifth generation mobile communication. It has the advantages of high capacity, high spectral efficiency, low power consumption, better coverage and open architecture. Time delay estimation is one of the hotspots in the field of communication, which directly determines the overall performance of D-MIMO antenna system. Signal processing operations such as signal detection, channel equalization and demodulation depend on timing synchronization and channel estimation, which are closely related to time delay estimation. The channel environment is usually multipath, and the current leading based frame synchronization method is used to estimate the time delay in the case of the first path being the main path and the power being high. The position of impulse response in channel estimation is the estimated multipath relative delay. Therefore, this paper will explore the time delay estimation of distributed MIMO antenna systems from two aspects: multipath delay estimation and frame synchronization. Distributed compressed sensing (Distributed Compressed) is an extension of compression sensing. There are mainly three joint sparse models and their reconstruction algorithms for the difference of joint sparsity of multiple signals, which can realize the joint reconstruction estimation of multiple signals with fewer observations. ADMM (Alternating Direction Method of Multipliers) has been well applied to the joint estimation of multiple sparse channels in communication systems. ADMM (Alternating Direction Method of Multipliers) is a popular optimization method for distributed parallel computing, which can achieve approximate optimal solution in each iteration and high computation speed. For distributed MIMO antenna systems, the multipath delay estimation is not accurate, the computational complexity is large, the resolution is not enough, and so on. Considering the correlation and sparsity of multipath channel, a DCS multipath time delay estimation method based on ADMM is proposed in this paper. It includes the establishment of the estimation model, the determination of the objective function and the calculation of the algorithm. The simulation results show that the proposed method not only has better time delay estimation performance, but also improves the resolution, saves the number of measurements and reduces the computational complexity. In the traditional frame synchronization algorithm for estimating the first path arrival delay in distributed MIMO antenna systems, the traversal search method is generally used to determine the correct synchronization index points, which has the problem of large computational complexity and computational complexity. The golden section method is an approximate optimal strategy for solving the one-dimensional minimization problem and has the characteristics of low computational complexity. In this paper, a novel timing synchronization algorithm based on golden section method is proposed to solve the problem that the classical algorithm of timing synchronization estimation has a large amount of traversal search and computation based on the geometric characteristics of the synchronization metric curve. Taking frame synchronization and its application in distributed MIMO system as an example, the algorithm flow and complexity analysis are given. The simulation results show that the proposed method still keeps the same performance as the traditional algorithm under the condition of greatly reducing the complexity.
【學(xué)位授予單位】：湘潭大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN919.3

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