本文選題：智能天線　切入點：自適應(yīng)波束形成　出處：《東北大學(xué)》2014年碩士論文

【摘要】：智能天線技術(shù)作為現(xiàn)代通信領(lǐng)域的研究熱點,已成功的應(yīng)用到無線通信系統(tǒng)中。智能天線引進了空分多址技術(shù),能夠與其他多址技術(shù)相結(jié)合,使通信資源由時間域、頻率域、碼域擴展到空間域,有效地增大了系統(tǒng)的容量,最大限度的利用有限的頻譜資源,并將會在未來移動通信系統(tǒng)中發(fā)揮重要作用。自適應(yīng)波束形成技術(shù)是智能天線的核心技術(shù),它能夠自適應(yīng)地控制天線陣方向圖在用戶信號方向產(chǎn)生高增益窄波束,在干擾信號方向產(chǎn)生較深的零陷,是實現(xiàn)用戶信號最佳接收的有效方法。本文圍繞自適應(yīng)波束形成算法展開研究,在總結(jié)前人工作的基礎(chǔ)上,提出了一些改進算法,主要工作如下：首先,本文對目前國內(nèi)外智能天線技術(shù)及自適應(yīng)波束形成算法的研究現(xiàn)狀進行了綜述,并介紹了自適應(yīng)波束形成技術(shù)中的最佳加權(quán)準則。其次,本文研究了經(jīng)典的最小均方(Least Mean Square, LMS)算法,并對SVSLMS算法和MSVSLMS算法進行了重點仿真研究和數(shù)學(xué)分析,針對這兩種算法的缺陷提出了一種改進的算法,該算法是基于雙曲余弦函數(shù)的變步長LMS算法,通過定義新的步長函數(shù),改進了上述算法的缺點,仿真結(jié)果證明了所提出算法的有效性。再次,本文詳細分析了周期自適應(yīng)波束形成(Cyclic Adaptive Beamforming, CAB)類算法,其中約束周期自適應(yīng)波束形成算法(Constrained CAB, CCAB)在低信號干擾噪聲比情況下性能很差,為解決上述問題,本文提出一種改進的基于特征空間的CAB算法(ECAB),該算法利用信號子空間約束來提高算法的魯棒性。大量的計算機仿真實驗驗證了本文改進算法的有效性。最后,對本文的研究工作進行了總結(jié),并對未來的研究工作進行了展望。
[Abstract]:As a research hotspot in modern communication field, smart antenna technology has been successfully applied to wireless communication systems.Smart antenna introduces space division multiple access (SDMA) technology, which can combine with other multiple access technologies to extend communication resources from time domain, frequency domain and code domain to space domain, which effectively increases the capacity of the system and maximizes the use of limited spectrum resources.And will play an important role in the future mobile communication system.Adaptive beamforming is the core technology of smart antenna. It can adaptively control the antenna array pattern to produce high gain narrow beam in the direction of user signal and deep zero trapping in the direction of interference signal.It is an effective method to realize the optimal reception of user signal.In this paper, the adaptive beamforming algorithm is studied. On the basis of summarizing the previous work, some improved algorithms are proposed. The main work is as follows: first,In this paper, the research status of smart antenna technology and adaptive beamforming algorithm at home and abroad is reviewed, and the optimal weighting criterion in adaptive beamforming technology is introduced.Secondly, this paper studies the classical least mean square Mean squared (LMS) algorithm, and focuses on the simulation and mathematical analysis of SVSLMS algorithm and MSVSLMS algorithm, and proposes an improved algorithm for the defects of these two algorithms.This algorithm is a variable step size LMS algorithm based on hyperbolic cosine function. By defining a new step size function, the shortcomings of the above algorithm are improved. The simulation results show that the proposed algorithm is effective.Thirdly, the periodic adaptive beamforming algorithm, cyclic Adaptive beam forming algorithm, is analyzed in detail. The constrained periodic adaptive beamforming algorithm (CCABs) has poor performance in the case of low signal interference noise ratio.An improved feature space-based CAB algorithm is proposed in this paper. The algorithm uses signal subspace constraints to improve the robustness of the algorithm.A large number of computer simulation experiments verify the effectiveness of the improved algorithm.Finally, the research work of this paper is summarized, and the future research work is prospected.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN821.91

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