基于高阶累积量的大气激光通信信道盲均衡的研究
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摘要
大气激光通信是指利用激光束作为载体在大气中进行语音、数据、图像信息双向传送的一种技术,它在解决“最后一公里”问题、应急通信等方面有着良好的应用前景。
尽管大气激光通信身兼无线和宽带这两个特点,但同时这种以大气为媒介,激光为载波的点对点式通信技术,有其自身不可避免的缺点,激光在大气中传输会受到大气信道中各种因素的影响,引起信号衰减和符号间干扰,导致误码率增加。为了保证激光通信链路的正常、可靠运行,研究克服大气信道传输因素对激光传输影响的技术具有非常重要的意义。
本文采用盲均衡技术来解决大气激光通信中的符号间干扰问题。首先简要介绍了大气激光通信系统及其特点,分析了国内外研究机构在大气激光通信方面的研究现状,然后根据大气激光通信的特点,提出了大气激光通信系统中的盲均衡方案,对隐含和直接使用高阶统计量的盲均衡算法的性能进行了研究。研究内容主要包括以下几个方面:
1.研究了Bussgang类盲均衡算法的数学模型及其相关算法,包括Sato算法、Godard算法和判决引导算法;提出了判决引导法与基于累积量的自适应滤波算法相结合的盲均衡算法,并对该算法进行仿真。仿真结果表明,该算法可获得较小于判决引导法的剩余均方误差,但由于此算法计算量较大,不利于实时均衡。
2.研究了几种直接使用高阶累积量的算法,包括基于三阶累积量的奇数阶(三、二阶)归一化法和直接法,分析了这几种算法的性能,通过仿真比较可知,直接法收敛速度较快,该算法使用较长数据对信道特性初始值估计时,可获得更好的均衡效果;而基于奇数阶(三、二阶)归一化算法实现较为简单,算法稳定性较好。
3.针对在不同天气状况下的大气激光通信信道对信号传输的影响不同,利用实际测量功率值模拟大气激光信道对几种算法进行仿真,并对算法性能进行了比较和评估。
Atmosphere Laser Communication (ALC) refers to the technology of transmitting voice, data and graphics using laser bean. Because of its advantage of narrow transmission bean, small antenna size, broad information capability and high performance to price, it impressed many people in communication area. So it has good application foreground in resolve of "The Last Kilometer Problem" and emergence communication.
Although the Atmosphere Laser Communication has the two characteristics of board-band and wireless, this point to-point communication based atmosphere channel and medium of laser have inevitable defect itself. The transmission of laser in atmosphere was affected by kinds of factors in atmosphere channel. It brought signal attenuation and inter-symbol interferences. It leaded the addition of bit error rate. Approach the technique of being against the effect of atmosphere channel transmission factor to ladder transmission for ensure the normal of laser communication link have a very important meaning.
This paper solved the problem about signal attenuation and ISI in the ALC system through blind equalization technique. Firstly, the dissertation introduced the Atmosphere Laser Communication system and its characteristic simply, and then the scheme about research of blind equalization in atmosphere laser communication system was advanced. The dissertation focuses on the performance of blind equalization using higher-order statistics implicitly and explicitly in accordance according the characteristic of Atmosphere Laser Communication channel. The research consists of several aspects as follows:
1.The mathematics' model of Bussgang BE and its relevant algorithm including Sato alg--orithm, Godard algorithm and DD(Decision-Directed) algorithm is discussed in our research, and the adaptive CDLMS filter base third-order cumulant algorithm, combining the conventional blind equalization algorithm with the decision direction, is presented. Furthermore, the result from the simulation about that algorithm which is presented in this paper is that the smaller steady-state error results from these algorithms than the DD (Decision-Directed) algorithm.
2.The explicitly cumulant algorithms and the even-order normalized cumulant algorithm's is studied. The result of simulation about performance of these algorithm is that the rapidity of convergence of the explicitly cumulant algorithms is faster than the even-order normalized cumulant algorithms; the stability of the even-order normalized cumulant algorithms is very good.
3.According to the problem of the different effect on the signal transmission by different the weather regime, The ALC channel is analog, using the data measuring from the ALC system. We demonstrate the efficiency of several blind equalization algorithms based the analogic ALC channel, including comparison study and evaluation of their performance.
尽管大气激光通信身兼无线和宽带这两个特点,但同时这种以大气为媒介,激光为载波的点对点式通信技术,有其自身不可避免的缺点,激光在大气中传输会受到大气信道中各种因素的影响,引起信号衰减和符号间干扰,导致误码率增加。为了保证激光通信链路的正常、可靠运行,研究克服大气信道传输因素对激光传输影响的技术具有非常重要的意义。
本文采用盲均衡技术来解决大气激光通信中的符号间干扰问题。首先简要介绍了大气激光通信系统及其特点,分析了国内外研究机构在大气激光通信方面的研究现状,然后根据大气激光通信的特点,提出了大气激光通信系统中的盲均衡方案,对隐含和直接使用高阶统计量的盲均衡算法的性能进行了研究。研究内容主要包括以下几个方面:
1.研究了Bussgang类盲均衡算法的数学模型及其相关算法,包括Sato算法、Godard算法和判决引导算法;提出了判决引导法与基于累积量的自适应滤波算法相结合的盲均衡算法,并对该算法进行仿真。仿真结果表明,该算法可获得较小于判决引导法的剩余均方误差,但由于此算法计算量较大,不利于实时均衡。
2.研究了几种直接使用高阶累积量的算法,包括基于三阶累积量的奇数阶(三、二阶)归一化法和直接法,分析了这几种算法的性能,通过仿真比较可知,直接法收敛速度较快,该算法使用较长数据对信道特性初始值估计时,可获得更好的均衡效果;而基于奇数阶(三、二阶)归一化算法实现较为简单,算法稳定性较好。
3.针对在不同天气状况下的大气激光通信信道对信号传输的影响不同,利用实际测量功率值模拟大气激光信道对几种算法进行仿真,并对算法性能进行了比较和评估。
Atmosphere Laser Communication (ALC) refers to the technology of transmitting voice, data and graphics using laser bean. Because of its advantage of narrow transmission bean, small antenna size, broad information capability and high performance to price, it impressed many people in communication area. So it has good application foreground in resolve of "The Last Kilometer Problem" and emergence communication.
Although the Atmosphere Laser Communication has the two characteristics of board-band and wireless, this point to-point communication based atmosphere channel and medium of laser have inevitable defect itself. The transmission of laser in atmosphere was affected by kinds of factors in atmosphere channel. It brought signal attenuation and inter-symbol interferences. It leaded the addition of bit error rate. Approach the technique of being against the effect of atmosphere channel transmission factor to ladder transmission for ensure the normal of laser communication link have a very important meaning.
This paper solved the problem about signal attenuation and ISI in the ALC system through blind equalization technique. Firstly, the dissertation introduced the Atmosphere Laser Communication system and its characteristic simply, and then the scheme about research of blind equalization in atmosphere laser communication system was advanced. The dissertation focuses on the performance of blind equalization using higher-order statistics implicitly and explicitly in accordance according the characteristic of Atmosphere Laser Communication channel. The research consists of several aspects as follows:
1.The mathematics' model of Bussgang BE and its relevant algorithm including Sato alg--orithm, Godard algorithm and DD(Decision-Directed) algorithm is discussed in our research, and the adaptive CDLMS filter base third-order cumulant algorithm, combining the conventional blind equalization algorithm with the decision direction, is presented. Furthermore, the result from the simulation about that algorithm which is presented in this paper is that the smaller steady-state error results from these algorithms than the DD (Decision-Directed) algorithm.
2.The explicitly cumulant algorithms and the even-order normalized cumulant algorithm's is studied. The result of simulation about performance of these algorithm is that the rapidity of convergence of the explicitly cumulant algorithms is faster than the even-order normalized cumulant algorithms; the stability of the even-order normalized cumulant algorithms is very good.
3.According to the problem of the different effect on the signal transmission by different the weather regime, The ALC channel is analog, using the data measuring from the ALC system. We demonstrate the efficiency of several blind equalization algorithms based the analogic ALC channel, including comparison study and evaluation of their performance.
引文
[1]安毓英.激光传输技术[J].激光与红外,2002,32(6):435-438
[2]丁德强.大气激光通信PPM调制解调系统设计[D].西安:西安理工大学,2005:2-8
[3]周学文.大气激光通信系统中的时域均衡研究[D].西安:西安理工大学,2006:2-5
[4]邱天爽,魏东兴.通信中的自适应信号处理[M].北京:电子工业出版社,2005:123-124
[5]Y.Sato.A method of self-recovering equalization for multilevel amplitude-modulation systems [J].IEEE Transactions on Communications,June 1975,23:679-682
[6]D.N.Godard.Self-recovering equalization and varrier tracking in two-dimensional data communica-tionsystems[J].IEEE Transactions on Communications,1980,28(11):1867-1875
[7]R.W.Lucky.Techniques for adaptive equalization of digital communication systems[J].Bell Syse-ms Technical Journal,Feb 1996,45(2):255-286
[8]A.Benveniste.Phase System;M.Goursat,G.Ruget.Robust Identification of a Nonminimum Blind Adj-ustment of a Linear equalizer in Data Communication[J].IEEE Trans on automatic control,1980,25:385-399
[9]张立毅,张雄.基于Bussgang技术的盲均衡算法分析[J].计算机工程与应用,2003,35:74-76.
[10]Proakis J G,Niakias C L.Blind equalization[J].Adaptive Signal Processing,1991,15:76-81
[11]Godard D.Self recovering equalization and carrier tracking in two-dimensional data Communicatio-n systems[J].IEEE Trans.Commun,1980,28:1867-1875
[12]Halzinakos D,Nikias C L.Blind decision feedback equalization structures based on adaptive cumuland techniqes[J].ICC,1989,89:1278-1282
[13]Xiaohua Li.Blind Channel Estimation and Equalization in Wireless Sensor Networks Based on Correlations Among Sensors[J].IEEE transactions on signal processing,April 2005,53(4):1511-1519
[14]王宁才.数据通信系统中的盲均衡研究[D].吉林:吉林大学,2006:8-12
[15]A.Benweniste.Analysis of Stochastic Approximation Scheme with Disconti-nuous and Dependent Forcing Terms with Applications to Data Communicanon Algorithms[J].IEEE Trans On AC,1980,25:1042-1058.
[16]D Hatzinakos,C L Nikias.Blind equalization using a tricepstrum based algorithm[J].IEEE Trans on communication,1991,39:669-682
[17]Porat B,Friedlander B.Blind equalization of digital communication channels using high-order moments[J].IEEE Trans on Signal Process,1991,39:522-526
[18]Cadzow J A.Blind deconvolution via cumulant extrema[J].IEEE Signal Processing,1996,13(3):24-42
[19]李翠萍,谢红卫.基于高阶累积量方法的非高斯非最小相位.ARMA模型辨识[J].上海大学学报,Oct 2001,7(5):438-441
[20]柯熙政,席晓莉.无线激光通信概论[M].北京:北京邮电大学出版社,2004:239-244
[21]何海平,计时鸣,张利.基于高阶统计量的信号分析与处理[J].Mechanical Electrical Engineering Magazine,2003,20(5):85-86
[22]张晓琴.基于高阶谱理论盲均衡算法的研究[D].太原:太原理工大学,2003:14-22
[23]张贤达.现代信号处理[M].北京:消华大学出版社,1994:263-274
[24]Leonov V P,Shiryaev A N.On a method of calculation semi-invariants[J].Theor.Prob,Apl 1959,4:319-329
[25]李刚.通信系统中盲均衡技术的研究[D].吉林:吉林大学,2004:28-30
[26]Brillinger D B.An introduction to polyspectra[J].Ann.Math.Statist.,1965,36:1351-1374
[27]Brillinger D B Rosenblantt M.Asymptotic theory of estimtes of k-th order spectra[J].In Harries ed Spectral analysis of time series New York Wiley,1967,20:153-188
[28]Brillinger D B.The identification of a particular nonlinear time series system[J].Biometrik,1977,64:509-515
[29]高鹰.基于累积量的自适应滤波理论及其应用[D].广州:华南理工大学,2002:24-26
[30]Nikias C L,M R Raghuveer.Bispectrum Estimation A digital signal processing framework[J].Proceedings IEEE,1987,75(7):869-891
[31]Rosenblantt M.Van Ness J W.Estimtion of the bispectrum[J].Ann.Math.Statist.,1965,36:1120-1136
[32]张贤达.时间序列分析高阶统计量方法[M].北京:清华大学出版社,1996:17-20
[33]Rosenblantt M Van Ness J W.Estimtion of the bispectrum[J].Ann Math.Statist,1965,36:1120-1136
[34]Giannakis G B.Cumulants A powerful tool in signal processing[J].Proc of the IEEE,1987,75(3):1333-1334
[35]邹谋炎.反卷积和信号复原[M].北京:国防工业出版社,2001:45-59
[36]Zhang X D,Zhang Y S.FIR system identification using higher eumulants alone[J].IEEE Trans Signal Processing,1994,42:2854-2858
[37]Mendei J M,Swanmi A.Cumulant-based approach to the harmonic retrieval and related problems [J].IEEE Trans Signal Processing,1991,39:1099-1109
[38]Zheng F C,et al.Cumulant based deconvolution and identification several new families of linear equations[J].Signal Processing,Jan 1993,30(2):199-219
[39]Zheng F C,Mclaughlin S and Mulgrew B.Blind equalization of non minimum phase channels high-er order cumulant based algorithm[J].IEEE Trans on Signal processing,1993,41(2):681-691
[40]Proakis J G.Digital communications[M].Mc:Graw-Hill,1983:121-138
[41]赵成林.基于高阶统计量的系统参数估计与盲均衡算法的研究[D].北京:北京邮电大学,1997: 12-35
[42]John G Proakis等著.现代通信系统(MATLAB版)(第二版)[M].北京:电子工业出版社,2005:89-101
[43]张立毅,梁静毅.实数系统中三二阶归一化累积量盲均衡算法的研究[J].电路与系统学报,2007,12(1):78-81
[44]张贤达,保铮.通信信号处理[M].北京:国防工业出版社,2000:277-281
[45]Bussgang J J.Cross correlation functions of amplitude-distorted Guassian signals[D].Tech.Rep 216:MIT Research Laboratory of Electronics,1952:23-34
[46]Barratt J F,Lampard D G.An expansion for some second-order probability distributions and its app-lication to noise problems[J].IRE Trans Inform.Theory,1955,1:10-15
[47]Sato,Y.A Method of Self-Recovering Equalization for Multilevel Amplitude-Modulation Systems Communications[J].IEEE Transactions on legacy,1975,23(6):679-682
[48]王峰.基于高阶统计量的水声信道盲均衡理论与算法[D].西安:西北工业大学,2003:18-44
[49]Godard D.Self-recovering equalization and carrier-tracking in two-dimendional data communicato-nsystems[J].IEEE Trans Commun,1980,28:1867-1875
[50]R W Lucky.Techniques for adaptive equalization of digital communication systems[J].Bell S-ystems Technical Journal,1966,45(2):255-286
[51]Picchi,G and Prati,G.Blind Equalization and Carrier Recovery Using a Stop-and-Go DecisionDirected Algorithm[J].Communications IEEE Transactions on legacy,1988,35(9):877-887
[52]Benveniste,A and Goursat,M..Blind Equalizers Communications[J],IEEE Transactions on leg-acy,1984,32(8):871-883
[53]Deshpande,N.Fast recovery equalization techniques for DTV signals[J].Broadcasting Transa-ctions on,1997,43(4):370-377
[54]张益萍.基于FPGA的盲均衡器的设计[D].西安:西北工业大学,2004:26-28
[55]Feng C C,Hsi C H,and Chi C Y.Performance of Shalvi and Weinsteins blind deconvolution criteria for channels with without zeros on the unit circle[J].IEEE SP Workshop on SPAWC,1999,12:82-85
[56]GAO Ying,XIE Sheng-li.A class of cumulant domain adaptive filtering algorithms[J].Journal of Guangzhou,2003,2(2):126-130
[57]尚万峰,关惠玲,李志军.基于高阶累积量自适应滤波的故障特征的提取[J].信号处理,2005,21(5):544-547
[58]陈丽新.大气激光通信系统的实验测量[D].西交:西安西安理工大学,2005:42-47
[2]丁德强.大气激光通信PPM调制解调系统设计[D].西安:西安理工大学,2005:2-8
[3]周学文.大气激光通信系统中的时域均衡研究[D].西安:西安理工大学,2006:2-5
[4]邱天爽,魏东兴.通信中的自适应信号处理[M].北京:电子工业出版社,2005:123-124
[5]Y.Sato.A method of self-recovering equalization for multilevel amplitude-modulation systems [J].IEEE Transactions on Communications,June 1975,23:679-682
[6]D.N.Godard.Self-recovering equalization and varrier tracking in two-dimensional data communica-tionsystems[J].IEEE Transactions on Communications,1980,28(11):1867-1875
[7]R.W.Lucky.Techniques for adaptive equalization of digital communication systems[J].Bell Syse-ms Technical Journal,Feb 1996,45(2):255-286
[8]A.Benveniste.Phase System;M.Goursat,G.Ruget.Robust Identification of a Nonminimum Blind Adj-ustment of a Linear equalizer in Data Communication[J].IEEE Trans on automatic control,1980,25:385-399
[9]张立毅,张雄.基于Bussgang技术的盲均衡算法分析[J].计算机工程与应用,2003,35:74-76.
[10]Proakis J G,Niakias C L.Blind equalization[J].Adaptive Signal Processing,1991,15:76-81
[11]Godard D.Self recovering equalization and carrier tracking in two-dimensional data Communicatio-n systems[J].IEEE Trans.Commun,1980,28:1867-1875
[12]Halzinakos D,Nikias C L.Blind decision feedback equalization structures based on adaptive cumuland techniqes[J].ICC,1989,89:1278-1282
[13]Xiaohua Li.Blind Channel Estimation and Equalization in Wireless Sensor Networks Based on Correlations Among Sensors[J].IEEE transactions on signal processing,April 2005,53(4):1511-1519
[14]王宁才.数据通信系统中的盲均衡研究[D].吉林:吉林大学,2006:8-12
[15]A.Benweniste.Analysis of Stochastic Approximation Scheme with Disconti-nuous and Dependent Forcing Terms with Applications to Data Communicanon Algorithms[J].IEEE Trans On AC,1980,25:1042-1058.
[16]D Hatzinakos,C L Nikias.Blind equalization using a tricepstrum based algorithm[J].IEEE Trans on communication,1991,39:669-682
[17]Porat B,Friedlander B.Blind equalization of digital communication channels using high-order moments[J].IEEE Trans on Signal Process,1991,39:522-526
[18]Cadzow J A.Blind deconvolution via cumulant extrema[J].IEEE Signal Processing,1996,13(3):24-42
[19]李翠萍,谢红卫.基于高阶累积量方法的非高斯非最小相位.ARMA模型辨识[J].上海大学学报,Oct 2001,7(5):438-441
[20]柯熙政,席晓莉.无线激光通信概论[M].北京:北京邮电大学出版社,2004:239-244
[21]何海平,计时鸣,张利.基于高阶统计量的信号分析与处理[J].Mechanical Electrical Engineering Magazine,2003,20(5):85-86
[22]张晓琴.基于高阶谱理论盲均衡算法的研究[D].太原:太原理工大学,2003:14-22
[23]张贤达.现代信号处理[M].北京:消华大学出版社,1994:263-274
[24]Leonov V P,Shiryaev A N.On a method of calculation semi-invariants[J].Theor.Prob,Apl 1959,4:319-329
[25]李刚.通信系统中盲均衡技术的研究[D].吉林:吉林大学,2004:28-30
[26]Brillinger D B.An introduction to polyspectra[J].Ann.Math.Statist.,1965,36:1351-1374
[27]Brillinger D B Rosenblantt M.Asymptotic theory of estimtes of k-th order spectra[J].In Harries ed Spectral analysis of time series New York Wiley,1967,20:153-188
[28]Brillinger D B.The identification of a particular nonlinear time series system[J].Biometrik,1977,64:509-515
[29]高鹰.基于累积量的自适应滤波理论及其应用[D].广州:华南理工大学,2002:24-26
[30]Nikias C L,M R Raghuveer.Bispectrum Estimation A digital signal processing framework[J].Proceedings IEEE,1987,75(7):869-891
[31]Rosenblantt M.Van Ness J W.Estimtion of the bispectrum[J].Ann.Math.Statist.,1965,36:1120-1136
[32]张贤达.时间序列分析高阶统计量方法[M].北京:清华大学出版社,1996:17-20
[33]Rosenblantt M Van Ness J W.Estimtion of the bispectrum[J].Ann Math.Statist,1965,36:1120-1136
[34]Giannakis G B.Cumulants A powerful tool in signal processing[J].Proc of the IEEE,1987,75(3):1333-1334
[35]邹谋炎.反卷积和信号复原[M].北京:国防工业出版社,2001:45-59
[36]Zhang X D,Zhang Y S.FIR system identification using higher eumulants alone[J].IEEE Trans Signal Processing,1994,42:2854-2858
[37]Mendei J M,Swanmi A.Cumulant-based approach to the harmonic retrieval and related problems [J].IEEE Trans Signal Processing,1991,39:1099-1109
[38]Zheng F C,et al.Cumulant based deconvolution and identification several new families of linear equations[J].Signal Processing,Jan 1993,30(2):199-219
[39]Zheng F C,Mclaughlin S and Mulgrew B.Blind equalization of non minimum phase channels high-er order cumulant based algorithm[J].IEEE Trans on Signal processing,1993,41(2):681-691
[40]Proakis J G.Digital communications[M].Mc:Graw-Hill,1983:121-138
[41]赵成林.基于高阶统计量的系统参数估计与盲均衡算法的研究[D].北京:北京邮电大学,1997: 12-35
[42]John G Proakis等著.现代通信系统(MATLAB版)(第二版)[M].北京:电子工业出版社,2005:89-101
[43]张立毅,梁静毅.实数系统中三二阶归一化累积量盲均衡算法的研究[J].电路与系统学报,2007,12(1):78-81
[44]张贤达,保铮.通信信号处理[M].北京:国防工业出版社,2000:277-281
[45]Bussgang J J.Cross correlation functions of amplitude-distorted Guassian signals[D].Tech.Rep 216:MIT Research Laboratory of Electronics,1952:23-34
[46]Barratt J F,Lampard D G.An expansion for some second-order probability distributions and its app-lication to noise problems[J].IRE Trans Inform.Theory,1955,1:10-15
[47]Sato,Y.A Method of Self-Recovering Equalization for Multilevel Amplitude-Modulation Systems Communications[J].IEEE Transactions on legacy,1975,23(6):679-682
[48]王峰.基于高阶统计量的水声信道盲均衡理论与算法[D].西安:西北工业大学,2003:18-44
[49]Godard D.Self-recovering equalization and carrier-tracking in two-dimendional data communicato-nsystems[J].IEEE Trans Commun,1980,28:1867-1875
[50]R W Lucky.Techniques for adaptive equalization of digital communication systems[J].Bell S-ystems Technical Journal,1966,45(2):255-286
[51]Picchi,G and Prati,G.Blind Equalization and Carrier Recovery Using a Stop-and-Go DecisionDirected Algorithm[J].Communications IEEE Transactions on legacy,1988,35(9):877-887
[52]Benveniste,A and Goursat,M..Blind Equalizers Communications[J],IEEE Transactions on leg-acy,1984,32(8):871-883
[53]Deshpande,N.Fast recovery equalization techniques for DTV signals[J].Broadcasting Transa-ctions on,1997,43(4):370-377
[54]张益萍.基于FPGA的盲均衡器的设计[D].西安:西北工业大学,2004:26-28
[55]Feng C C,Hsi C H,and Chi C Y.Performance of Shalvi and Weinsteins blind deconvolution criteria for channels with without zeros on the unit circle[J].IEEE SP Workshop on SPAWC,1999,12:82-85
[56]GAO Ying,XIE Sheng-li.A class of cumulant domain adaptive filtering algorithms[J].Journal of Guangzhou,2003,2(2):126-130
[57]尚万峰,关惠玲,李志军.基于高阶累积量自适应滤波的故障特征的提取[J].信号处理,2005,21(5):544-547
[58]陈丽新.大气激光通信系统的实验测量[D].西交:西安西安理工大学,2005:42-47