本文關(guān)鍵詞：適用于超寬帶信號的多核稀疏字典構(gòu)造及應(yīng)用　出處：《山東大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 脈沖超寬帶 壓縮感知 多核稀疏字典 信道估計(jì)

【摘要】：作為采樣的重要理論依據(jù),奈奎斯特定理指出：采樣速率至少為信號最高頻率的兩倍才可能精確重構(gòu)出原始信號。隨著信息時(shí)代的到來,超寬帶技術(shù)以抗多徑衰落、低截獲率、低功耗、安全性能高等諸多優(yōu)點(diǎn)得到了廣泛的關(guān)注與應(yīng)用。由于其極寬的帶寬,接收機(jī)需要極高速率的模數(shù)轉(zhuǎn)換器(ADC)對信號進(jìn)行采樣,加上多徑信道復(fù)雜性,以奈奎斯特理論為依據(jù)的采樣方法難以得到實(shí)現(xiàn)。因此,超寬帶信號的采樣問題對超寬帶系統(tǒng)的發(fā)展造成了一定的阻礙。由Donoho、Cands等人提出的壓縮感知(Compressive Sensing,CS)采用一種異于傳統(tǒng)的方法,為超寬帶信號的采樣提供了新的途徑。它的特點(diǎn)是以遠(yuǎn)低于奈奎斯特速率的采樣速率對信號進(jìn)行采樣,在該理論框架下,采樣速率不再被信號的帶寬所限制。本文的研究重點(diǎn)是壓縮感知理論中稀疏字典的構(gòu)造方法,提出了一種多核稀疏字典并應(yīng)用于超寬帶信道估計(jì)中。本文的主要工作有以下幾個(gè)方面：1.提出一種多核稀疏字典的構(gòu)造方法。該字典在基于單核的多徑分集稀疏字典的基礎(chǔ)上,進(jìn)一步采用部分原子導(dǎo)數(shù)波形構(gòu)造輔助稀疏字典,將二者聯(lián)合作為壓縮感知理論中的稀疏字典。通過仿真實(shí)驗(yàn)分析了多核字典的性能,結(jié)果表明：多核稀疏字典的相關(guān)系數(shù)性能顯著優(yōu)于單核稀疏字典,初步肯定了我們的設(shè)想是可行的,其中只含有一階導(dǎo)數(shù)的多核稀疏字典(即雙核稀疏字典)性能最優(yōu)。2.對雙核稀疏字典提出了兩種構(gòu)造方案。第一種方案分別取多徑分集稀疏字典和它的導(dǎo)數(shù)字典的奇數(shù)項(xiàng)構(gòu)成交叉一階導(dǎo)數(shù)字典,第二種方案分別取多徑分集稀疏字典和它的導(dǎo)數(shù)字典的前半部分構(gòu)成疊加一階導(dǎo)數(shù)字典。仿真分析表明：兩種雙核稀疏字典性能優(yōu)于多徑分集稀疏字典；其中,疊加一階導(dǎo)數(shù)稀疏字典的相關(guān)系數(shù)更大,重構(gòu)信號與原始信號的匹配度更高,字典的性能更好,有利于提高信號稀疏性、降低采樣率和減小重構(gòu)誤差。3.將疊加一階導(dǎo)數(shù)字典應(yīng)用到超寬帶系統(tǒng)的信道估計(jì)中。利用導(dǎo)頻信號輔助,采用壓縮感知對超寬帶信道進(jìn)行估計(jì),估計(jì)結(jié)果用于接收機(jī)相關(guān)解調(diào)。對CM1、CM3兩種信道模型中的信道估計(jì)性能進(jìn)行了仿真分析,結(jié)果表明：與多徑分集稀疏字典相比,采用多核稀疏字典進(jìn)行超寬帶信道估計(jì),可以獲得更好的誤碼率性能。
[Abstract]:As an important theoretical basis for sampling, sampling theorem of Nyquist pointed out: two times the rate of at least the highest frequency of the signal can accurately reconstruct the original signal. With the advent of the information age, the ultra wideband technology to anti multipath fading, low interception rate, low power consumption, high safety performance advantages has been widely concerned and applied due. The extremely wide bandwidth, the receiver needs very high rate analog-to-digital converter (ADC) sampling of the signal, plus the multipath channel complexity, taking Nyquist theory as the basis of the sampling method is difficult to be achieved. Therefore, the sampling problem of UWB signal caused some obstacles to the development of UWB system. By Donoho. Compressed sensing proposed by Cands et al. (Compressive Sensing, CS) by using a method different from the traditional, provides a new way for sampling UWB signals. It is characterized by much less than The sampling rate of the Nyquist rate sampling of the signal, under the framework of the theory, the sampling rate is not limited by the bandwidth of the signal. This study focuses on the construction method of compressed sensing theory in sparse dictionary, put forward a multi kernel sparse dictionary and its application in ultra wide band channel estimation. The main works of this paper are the following the following aspects: 1. proposed a method for constructing multiple kernel sparse dictionary. The dictionary based on sparse dictionary mononuclear multipath diversity on the part of the further construction of auxiliary atom derivative waveform sparse dictionary, combined the two as the compressed sensing theory in sparse dictionary. Through simulation analysis the performance of multi-core dictionary the results showed that the correlation coefficient of performance is significantly better than single kernel sparse dictionary multiple kernel sparse dictionary, preliminary affirm our idea is feasible, which contains only one order derivative The multiple kernel sparse Dictionary (i.e. sparse dictionary optimal performance of.2. dual core) put forward two kinds of scheme of dual sparse dictionary. Odd the first scheme were taken multipath diversity sparse dictionary and its derivative dictionary which cross derivative dictionary, second schemes of multi size diversity sparse dictionary and its derivative dictionary the first part of a superposition of a derivative dictionary. Simulation results show that: two kinds of dual core sparse dictionary outperforms the multipath diversity sparse dictionary; the correlation coefficient of superposition of a derivative of sparse dictionary more reconstructed signal and the original signal matching degree is higher, the better performance of the dictionary, is helpful to improve the sparse signal. To reduce the sampling rate, and reduce the reconstruction error of.3. superposition derivative dictionary applied to UWB channel estimation system. Using the pilot signal, using compressed sensing of UWB channel To estimate the estimation results for the receiver demodulation. The CM1, CM3 two channel model in the channel estimation performance is simulated. The results showed that: compared with the sparse multipath diversity dictionary, using multiple kernel sparse Dictionary of UWB channel estimation, can obtain better BER performance.

【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN925

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本文編號：1382947