確定性盲信道辨識算法研究
發(fā)布時間：2018-10-17 08:19
【摘要】：無線數(shù)字通信中,受多徑傳輸?shù)刃诺酪蛩氐挠绊?接收信號會存在碼間干擾,因此需要進行信道辨識以對其引起的信號畸變進行校正。無需或僅需少量已知符號的盲信道辨識技術(shù)得到廣泛關(guān)注,基于二階統(tǒng)計量(Second-Order Statistics,SOS)的盲信道辨識算法所需數(shù)據(jù)量小、算法復雜度低,是近年來盲信道辨識領(lǐng)域的研究熱點。本文以國防某重大科研項目為依托,深入研究更適于實際應用的SOS確定性盲辨識算法。全文主要工作與成果如下:1.結(jié)合SIMO信道模型,本文歸納總結(jié)出具有普適性的SOS盲辨識算法可辨識條件,即信道條件、信源條件和數(shù)據(jù)條件。深入研究信道零點分布與SOS確定性盲辨識算法的可辨識性關(guān)系,并進行了相關(guān)的理論分析與仿真實驗。2.針對SOS確定性全盲辨識算法對信道階數(shù)的估計精度依賴性較高這一特點,本文提出一種基于樣本排序的信道階數(shù)估計改進算法,算法通過建立與樣本數(shù)據(jù)對應的連續(xù)次序?qū)ΧS空間,利用階數(shù)欠估計時的特定圖形結(jié)構(gòu)估計信道階數(shù),改進算法有效地提升了原算法在較低信噪比下的估計性能。然后提出一種聯(lián)合信道辨識與均衡的階數(shù)估計算法,算法首先構(gòu)造具有凸形結(jié)構(gòu)的辨識代價函數(shù),而后提出新穎的加權(quán)最小二乘均衡準則并給出相關(guān)的理論分析,聯(lián)合同樣具有凸形結(jié)構(gòu)的辨識代價函數(shù)與均衡代價函數(shù),在達到算法全局最優(yōu)解時完成對信道階數(shù)的估計,仿真實驗表明:該算法在不同信道條件下的估計性能明顯優(yōu)于現(xiàn)有的其他階數(shù)估計算法,且性能穩(wěn)定可靠。3.針對SOS確定性全盲辨識算法對信道階數(shù)誤差魯棒性差的問題,本文首先對信道零點分布與階數(shù)過估計之間的聯(lián)系進行深入的理論分析,發(fā)現(xiàn)并證明了由階數(shù)過估計額外引入的“公零點”具有單位圓聚集特性,利用這一特性提出一種基于信道零點分布的盲辨識算法,該算法簡單實用且適用范圍廣。同時,將“公零點”的單位圓聚集特性與具有較低復雜度的改進CR算法相結(jié)合,在頻域范圍內(nèi)求解信道響應以提高算法在小樣本數(shù)據(jù)條件下的辨識性能,提出一種采用FFT方法的抗階數(shù)過估計盲辨識算法,仿真實驗表明:該算法具有較強的信道階數(shù)誤差魯棒性。4.針對全盲辨識算法無法辨識含公零點信道且對信道階數(shù)誤差敏感的問題,本文提出一種采用奇異值分解方法的半盲辨識算法,算法通過奇異值分解將信道矩陣分解為兩個矩陣乘積的形式,分別利用接收數(shù)據(jù)和已知符號實現(xiàn)信道辨識,仿真實驗驗證了所提算法的有效性。然后提出一種基于信道相關(guān)性的半盲辨識算法,算法利用接收數(shù)據(jù)構(gòu)造的相關(guān)矩陣與信道向量的正交關(guān)系建立約束方程,并利用少量已知符號以及改進的最小二乘準則建立額外的約束,最終通過最小二乘法得到信道響應的閉式解,該算法性能穩(wěn)健且辨識精度高,對信道噪聲及信道階數(shù)誤差均具有較強的魯棒性。
[Abstract]:In wireless digital communication, due to the influence of channel factors such as multipath transmission, the received signal will have inter-symbol interference (ISI), so channel identification is needed to correct the signal distortion caused by it. Blind channel identification without or only a small number of known symbols has received extensive attention. Blind channel identification algorithm based on second-order statistics (Second-Order Statistics,SOS) requires a small amount of data and has a low complexity. It is a hot topic in the field of blind channel identification in recent years. In this paper, based on a major research project of national defense, the SOS deterministic blind identification algorithm, which is more suitable for practical application, is studied in depth. The main work and results are as follows: 1. Combined with the SIMO channel model, this paper summarizes the identifiable conditions of SOS blind identification algorithm with universality, that is, channel condition, source condition and data condition. The relationship between channel zero distribution and the identifiability of SOS deterministic blind identification algorithm is studied, and relevant theoretical analysis and simulation experiments are carried out. 2. In view of the high accuracy dependence on channel order estimation of SOS deterministic all-blind identification algorithm, an improved channel order estimation algorithm based on sample ordering is proposed in this paper. By establishing the continuous sequence pair space corresponding to the sample data and using the special graph structure of order underestimation to estimate the channel order, the improved algorithm can effectively improve the estimation performance of the original algorithm under lower SNR. Then, an order estimation algorithm for joint channel identification and equalization is proposed. Firstly, the cost function with convex structure is constructed, and then a novel weighted least square equalization criterion is proposed and the related theoretical analysis is given. When the identification cost function and equalization cost function with convex structure are combined, the channel order is estimated when the global optimal solution of the algorithm is reached. The simulation results show that the performance of the proposed algorithm is better than that of other order estimation algorithms under different channel conditions, and the performance is stable and reliable. Aiming at the problem of poor robustness of SOS deterministic all-blind identification algorithm to channel order error, the relationship between channel zero distribution and order overestimation is analyzed in this paper. It is found and proved that the "common zero" introduced by order overestimation has the characteristic of unit circle aggregation. By using this property, a blind identification algorithm based on channel zero distribution is proposed. The algorithm is simple and practical and has a wide range of applications. At the same time, combining the unit circle aggregation of "common zero" with the improved CR algorithm with low complexity, the channel response is solved in the frequency domain to improve the identification performance of the algorithm under the condition of small sample data. A blind identification algorithm against order overestimation using FFT method is proposed. The simulation results show that the algorithm is robust to channel order error. 4. Aiming at the problem that the all-blind identification algorithm can not identify the channel with common zero point and is sensitive to channel order error, a semi-blind identification algorithm based on singular value decomposition (SVD) is proposed in this paper. The channel matrix is decomposed into the product of two matrices by singular value decomposition, and the channel identification is realized by using received data and known symbols, respectively. The simulation results show that the proposed algorithm is effective. Then a semi-blind identification algorithm based on channel correlation is proposed. The constraint equation is established by using the orthogonal relation between the correlation matrix constructed by the received data and the channel vector. Using a small number of known symbols and the improved least square criterion to establish additional constraints, the closed-form solution of the channel response is obtained by the least square method. The algorithm is robust in performance and high in identification accuracy. It is robust to channel noise and channel order error.
【學位授予單位】：解放軍信息工程大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN92
本文編號：2276066
[Abstract]:In wireless digital communication, due to the influence of channel factors such as multipath transmission, the received signal will have inter-symbol interference (ISI), so channel identification is needed to correct the signal distortion caused by it. Blind channel identification without or only a small number of known symbols has received extensive attention. Blind channel identification algorithm based on second-order statistics (Second-Order Statistics,SOS) requires a small amount of data and has a low complexity. It is a hot topic in the field of blind channel identification in recent years. In this paper, based on a major research project of national defense, the SOS deterministic blind identification algorithm, which is more suitable for practical application, is studied in depth. The main work and results are as follows: 1. Combined with the SIMO channel model, this paper summarizes the identifiable conditions of SOS blind identification algorithm with universality, that is, channel condition, source condition and data condition. The relationship between channel zero distribution and the identifiability of SOS deterministic blind identification algorithm is studied, and relevant theoretical analysis and simulation experiments are carried out. 2. In view of the high accuracy dependence on channel order estimation of SOS deterministic all-blind identification algorithm, an improved channel order estimation algorithm based on sample ordering is proposed in this paper. By establishing the continuous sequence pair space corresponding to the sample data and using the special graph structure of order underestimation to estimate the channel order, the improved algorithm can effectively improve the estimation performance of the original algorithm under lower SNR. Then, an order estimation algorithm for joint channel identification and equalization is proposed. Firstly, the cost function with convex structure is constructed, and then a novel weighted least square equalization criterion is proposed and the related theoretical analysis is given. When the identification cost function and equalization cost function with convex structure are combined, the channel order is estimated when the global optimal solution of the algorithm is reached. The simulation results show that the performance of the proposed algorithm is better than that of other order estimation algorithms under different channel conditions, and the performance is stable and reliable. Aiming at the problem of poor robustness of SOS deterministic all-blind identification algorithm to channel order error, the relationship between channel zero distribution and order overestimation is analyzed in this paper. It is found and proved that the "common zero" introduced by order overestimation has the characteristic of unit circle aggregation. By using this property, a blind identification algorithm based on channel zero distribution is proposed. The algorithm is simple and practical and has a wide range of applications. At the same time, combining the unit circle aggregation of "common zero" with the improved CR algorithm with low complexity, the channel response is solved in the frequency domain to improve the identification performance of the algorithm under the condition of small sample data. A blind identification algorithm against order overestimation using FFT method is proposed. The simulation results show that the algorithm is robust to channel order error. 4. Aiming at the problem that the all-blind identification algorithm can not identify the channel with common zero point and is sensitive to channel order error, a semi-blind identification algorithm based on singular value decomposition (SVD) is proposed in this paper. The channel matrix is decomposed into the product of two matrices by singular value decomposition, and the channel identification is realized by using received data and known symbols, respectively. The simulation results show that the proposed algorithm is effective. Then a semi-blind identification algorithm based on channel correlation is proposed. The constraint equation is established by using the orthogonal relation between the correlation matrix constructed by the received data and the channel vector. Using a small number of known symbols and the improved least square criterion to establish additional constraints, the closed-form solution of the channel response is obtained by the least square method. The algorithm is robust in performance and high in identification accuracy. It is robust to channel noise and channel order error.
【學位授予單位】：解放軍信息工程大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN92
【參考文獻】
相關(guān)期刊論文 前1條
1 代松銀;袁嗣杰;董書攀;;基于子空間分解的信道階數(shù)估計算法[J];電子學報;2010年06期
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