Blind equalization based on adaptive forgetting factor, recursive least squares (RLS) with constant modulus algorithm (CMA), is investigated. The cost function of CMA is simplified to meet the second norm form to ...Blind equalization based on adaptive forgetting factor, recursive least squares (RLS) with constant modulus algorithm (CMA), is investigated. The cost function of CMA is simplified to meet the second norm form to ensure the stability of RLS-CMA, and thus an improved RLS-CMA (RLS-SCMA) is established. To further improve its performance, a new adaptive forgetting factor RLS-SCMA (ARLS-SCMA) is proposed. In ARLS-SCMA, the forgetting factor varies with the output error of the blind equalizer during the iterative process, which leads to a faster convergence rate and a smaller steady-state error. The simulation results prove the effectiveness under the condition of the underwater acoustic channel.展开更多
A new blind equalization algorithm based on the modified constant modulus algorithm (MCMA) and dithered signederror constant modulus algorithm (DSE-CMA) is proposed. This dithered signed-error MCMA (DSE-MCMA) ca...A new blind equalization algorithm based on the modified constant modulus algorithm (MCMA) and dithered signederror constant modulus algorithm (DSE-CMA) is proposed. This dithered signed-error MCMA (DSE-MCMA) can not only reduce the computational complexity, but also recover the phase rotation in the complex channel. Simulation results have verified the analysis and indicated the good property of DSE-MCMA.展开更多
An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square er...An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.展开更多
The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a ...The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size( VSS) modified constant modulus algorithms( MC-MA) and modified decision directed modulus algorithms( MD DMA) is proposed to ameliorate the convergence speed and mean square error( MSE) performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.展开更多
Aiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algori...Aiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators' outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase.展开更多
Probabilistically shaped(PS)high-order quadrature amplitude modulation(QAM)signals are attractive to coherent optical communication due to increased spectral efficiency.However,standard digital signal processing algor...Probabilistically shaped(PS)high-order quadrature amplitude modulation(QAM)signals are attractive to coherent optical communication due to increased spectral efficiency.However,standard digital signal processing algorithms are not optimal to demodulate PS high-order QAM signals.Therefore,a compromise equalization is indispensable to compensate the residual distortion.Meanwhile,the performance of conventional blind equalization highly depends on the accurate amplitude radius and distribution of the signals.The PS high-order QAM signals make the issue worsen because of indistinct amplitude distributions.In this work,we proposed an optimized blind equalization by utilizing a peak-density K-means clustering algorithm to accurately track the amplitude radius and distribution.We experimentally demonstrated the proposed method in a PS 256-QAM coherent optical transmission system and achieved approximately 1 dB optical signal-to-noise ratio improvement at the bit error rate of 1×10^(−3).展开更多
We propose a novel hybrid algorithm of BP neural ytetwork and apply it to blind equalization.The algorithm combines the merits of Rosario algorithm and random optimization method. Its cost function has strict convex c...We propose a novel hybrid algorithm of BP neural ytetwork and apply it to blind equalization.The algorithm combines the merits of Rosario algorithm and random optimization method. Its cost function has strict convex character (after a threshold) and the algorithm converges much faster than the BPmethod[2], as an exalople, we evaluate its performance by using it into blind equalization. With the help ofHigher Order Culnulants (HOC), the blind equalization scheme converges much faster than the CMAalgorithm and superior to the Back-propagation,nethod[2] due to its ability of finding the optimal solutionwith relatively fewer iteration stops.展开更多
A kind of Combined Constant Modulus Algorithm (CCMA) is presented to compensate the defects of the Constant Modulus Algorithm (CMA) and the Sign Error CMA (SECMA). And CCMA is applied to the equalization of the underw...A kind of Combined Constant Modulus Algorithm (CCMA) is presented to compensate the defects of the Constant Modulus Algorithm (CMA) and the Sign Error CMA (SECMA). And CCMA is applied to the equalization of the underwater acoustic channel (UWAC). Based on the decision of the equalizer’s output, its iteration process switches between展开更多
An adaptive blind support vector machine equalizer(ABSVME) is presented in this paper.The method is based upon least square support vector machine(LSSVM),and stems from signal feature reconstruction idea.By oversa...An adaptive blind support vector machine equalizer(ABSVME) is presented in this paper.The method is based upon least square support vector machine(LSSVM),and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.展开更多
A special Modulation-Induced Cyclostationarity(MIC)scheme is designed for the identification and equaliza-tion of FIR Single-Input-Single-Output(SISO)channel,with the property that the transmit power is constant and t...A special Modulation-Induced Cyclostationarity(MIC)scheme is designed for the identification and equaliza-tion of FIR Single-Input-Single-Output(SISO)channel,with the property that the transmit power is constant and the re-ceiver needs only one antenna.The cyclic Wiener equalizer is presented based on the estimated channel.展开更多
Based on the constant modulus criterion, a new Widely Linear(WL) blind equalizer and a novel widely linear recursive least square constant modulus algorithm are proposed to improve the blind equalization performance f...Based on the constant modulus criterion, a new Widely Linear(WL) blind equalizer and a novel widely linear recursive least square constant modulus algorithm are proposed to improve the blind equalization performance for complex-valued noncircular signals. The new algorithm takes advantage of the WL filtering theory by taking full use of second-order statistical information of the complex-valued noncircular signals. Therefore, the weight vector contains the complete second-order information of the real and imaginary parts to decrease the residual inter-symbol interference effectively. Theoretical analysis and simulation results show that the proposed scheme can significantly improve the equalization performance for complex-valued noncircular signals compared with traditional blind equalization algorithms.展开更多
Some channel compensation techniques integrated into front-end of speech recognizer for improving channel robustness are described. These techniques include cepstral mean normalization, rasta processing and blind equa...Some channel compensation techniques integrated into front-end of speech recognizer for improving channel robustness are described. These techniques include cepstral mean normalization, rasta processing and blind equalization. Two standard channel frequency characteristics, G.712 and MIRS, are introduced as channel distortion references and a mandarin digit string recognition task is performed for evaluating and comparing the performance of these different methods. The recognition results show that in G.712 case blind equalization can achieve the best recognition performance while cepstral mean normalization outperforms the other methods in MIRS case which is capable of reaching a word error rate of 3.96%.展开更多
A novel Recurrent Neural Network(RNN) based blind equalization algorithm is proposed in the paper.For the first time, the conjugate gradient algorithm and a three point searching method are used in RNN training.Simu...A novel Recurrent Neural Network(RNN) based blind equalization algorithm is proposed in the paper.For the first time, the conjugate gradient algorithm and a three point searching method are used in RNN training.Simulation results show that our algorithm is suprior to the one proposed by Kechriotis and the Constant Modulus Algorithm.展开更多
A modified constant modulus algorithm (MCMA) for blind channel equalization is proposed by modifying the constant modulus error function. The MCMA is compared with the conventional constant modulus algorithm (CMA) for...A modified constant modulus algorithm (MCMA) for blind channel equalization is proposed by modifying the constant modulus error function. The MCMA is compared with the conventional constant modulus algorithm (CMA) for symbol-spaced equalization of 4PSK signals. The result shows that the performance of the MCMA is superior to that of the CMA in both convergence rate and intersymbol interference for frequency selective channels in noisy environments. Simulation results using 8PSK signals also demonstrate that a fractionally spaced equalizer can preserve performance over variations in symbol-timing phase, whereas a baud-rate equalizer cannot.展开更多
We present an adaptive algorithm for blind identification and equalization of single-input multiple-output (SIMO) FIR channels with second-order statistics. We first reformulate the blind channel identification prob...We present an adaptive algorithm for blind identification and equalization of single-input multiple-output (SIMO) FIR channels with second-order statistics. We first reformulate the blind channel identification problem into a low-rank matrix approximation solution based on the QR decomposition of the received data matrix. Then, a fast recursive algorithm is developed based on the bi-iterative least squares (Bi-LS) subspace tracking method. The new algorithm requires only a computational complexity of O(md2) at each iteration, or even as low as O(md) if only equalization is necessary, where m is the dimension of the received data vector (or the row rank of channel matrix) and d is the dimension of the signal subspace (or the column rank of channel matrix). To overcome the shortcoming of the back substitution, an inverse QR iteration algorithm for subspace tracking and channel equalization is also developed. The inverse QR iteration algorithm is well suited for the parallel implementation in the systolic array. Simulation results are presented to illustrate the effectiveness of the proposed algorithms for the channel identification and equalization.展开更多
In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI...In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deconvolution process is carried out with no training symbols and the channel’s coefficients are obviously unknown to the receiver, no actual indication can be given (via the mean square error (MSE) or ISI expression) during the deconvolution process whether the blind adaptive equalizer succeeded to remove the heavy ISI from the transmitted symbols or not. Up to now, the output of a convolution and deconvolution process was mainly investigated from the ISI point of view. In this paper, the output of a convolution and deconvolution process is inspected from the leading digit point of view. Simulation results indicate that for the 4PAM (Pulse Amplitude Modulation) and 16QAM (Quadrature Amplitude Modulation) input case, the number “1” is the leading digit at the output of a convolution and deconvolution process respectively as long as heavy ISI exists. However, this leading digit does not follow exactly Benford’s Law but follows approximately the leading digit (digit 1) of a Gaussian process for independent identically distributed input symbols and a channel with many coefficients.展开更多
Based on the peak to valley ratio(PTVR) of the average magnitude difference function(AMDF), we present a novel optical signal to noise ratio(OSNR) and symbol rate(SR) estimation method for commonly used auxili...Based on the peak to valley ratio(PTVR) of the average magnitude difference function(AMDF), we present a novel optical signal to noise ratio(OSNR) and symbol rate(SR) estimation method for commonly used auxiliary amplitude modulations(AAMs). Moreover, it is demonstrated that the influence of chromatic dispersion(CD)on the method can be mitigated by maximizing the PTVR of the AMDF with additional tunable dispersion compensators. The results of simulations show that the OSNR estimation error can be kept within 0.8 dB in the wide OSNR range of(12, 32) dB, while the SR estimation error is below 0.079% for four widely used10 Gsymbol/s AAM signals.展开更多
基金financially supported in part by the National Natural Science Foundation of China(Grant No.61201418)Fundamental Research Funds for the Central Universities(Grant No.DC12010218)Scientific and Technological Research Project for Education Department of Liaoning Province(Grant No.2010046)
文摘Blind equalization based on adaptive forgetting factor, recursive least squares (RLS) with constant modulus algorithm (CMA), is investigated. The cost function of CMA is simplified to meet the second norm form to ensure the stability of RLS-CMA, and thus an improved RLS-CMA (RLS-SCMA) is established. To further improve its performance, a new adaptive forgetting factor RLS-SCMA (ARLS-SCMA) is proposed. In ARLS-SCMA, the forgetting factor varies with the output error of the blind equalizer during the iterative process, which leads to a faster convergence rate and a smaller steady-state error. The simulation results prove the effectiveness under the condition of the underwater acoustic channel.
基金Supported by the National Natural Science Foundation of China (60372057)
文摘A new blind equalization algorithm based on the modified constant modulus algorithm (MCMA) and dithered signederror constant modulus algorithm (DSE-CMA) is proposed. This dithered signed-error MCMA (DSE-MCMA) can not only reduce the computational complexity, but also recover the phase rotation in the complex channel. Simulation results have verified the analysis and indicated the good property of DSE-MCMA.
基金Sponsored by the Nature Science Foundation of Jiangsu(BK2009410)
文摘An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.
基金Supported by the National Natural Science Foundation of China(6100201461101129+1 种基金6122700161072050)
文摘The problem of inter symbol interference( ISI) in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn't require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size( VSS) modified constant modulus algorithms( MC-MA) and modified decision directed modulus algorithms( MD DMA) is proposed to ameliorate the convergence speed and mean square error( MSE) performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.
基金co-supported by National Natural Science Foundation of China (No. 61101075)the Pre-research Foundation (No. 9140A24040710HK0126)Fundament Research Funds for the Central Universities (YWF-11-02-176)
文摘Aiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators' outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase.
基金This work was supported in part by the National Key R&D Program of China(No.2020YFB1805805)the National Natural Science Foundation of China(No.62075147).
文摘Probabilistically shaped(PS)high-order quadrature amplitude modulation(QAM)signals are attractive to coherent optical communication due to increased spectral efficiency.However,standard digital signal processing algorithms are not optimal to demodulate PS high-order QAM signals.Therefore,a compromise equalization is indispensable to compensate the residual distortion.Meanwhile,the performance of conventional blind equalization highly depends on the accurate amplitude radius and distribution of the signals.The PS high-order QAM signals make the issue worsen because of indistinct amplitude distributions.In this work,we proposed an optimized blind equalization by utilizing a peak-density K-means clustering algorithm to accurately track the amplitude radius and distribution.We experimentally demonstrated the proposed method in a PS 256-QAM coherent optical transmission system and achieved approximately 1 dB optical signal-to-noise ratio improvement at the bit error rate of 1×10^(−3).
文摘We propose a novel hybrid algorithm of BP neural ytetwork and apply it to blind equalization.The algorithm combines the merits of Rosario algorithm and random optimization method. Its cost function has strict convex character (after a threshold) and the algorithm converges much faster than the BPmethod[2], as an exalople, we evaluate its performance by using it into blind equalization. With the help ofHigher Order Culnulants (HOC), the blind equalization scheme converges much faster than the CMAalgorithm and superior to the Back-propagation,nethod[2] due to its ability of finding the optimal solutionwith relatively fewer iteration stops.
基金This work was supported by the National Defense Science & Technology Key Lab.(5144010201HK0302)
文摘A kind of Combined Constant Modulus Algorithm (CCMA) is presented to compensate the defects of the Constant Modulus Algorithm (CMA) and the Sign Error CMA (SECMA). And CCMA is applied to the equalization of the underwater acoustic channel (UWAC). Based on the decision of the equalizer’s output, its iteration process switches between
基金Supported by the National Natural Science Foundation of China(60772056)the Postdoctoral Science Foundation of China(20070421094)
文摘An adaptive blind support vector machine equalizer(ABSVME) is presented in this paper.The method is based upon least square support vector machine(LSSVM),and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.
文摘A special Modulation-Induced Cyclostationarity(MIC)scheme is designed for the identification and equaliza-tion of FIR Single-Input-Single-Output(SISO)channel,with the property that the transmit power is constant and the re-ceiver needs only one antenna.The cyclic Wiener equalizer is presented based on the estimated channel.
基金Supported by the National Natural Science Foundation of China(No.61072046)the Basic Scientific and Technological Frontier Project of Henan Province(No.1123004100322)
文摘Based on the constant modulus criterion, a new Widely Linear(WL) blind equalizer and a novel widely linear recursive least square constant modulus algorithm are proposed to improve the blind equalization performance for complex-valued noncircular signals. The new algorithm takes advantage of the WL filtering theory by taking full use of second-order statistical information of the complex-valued noncircular signals. Therefore, the weight vector contains the complete second-order information of the real and imaginary parts to decrease the residual inter-symbol interference effectively. Theoretical analysis and simulation results show that the proposed scheme can significantly improve the equalization performance for complex-valued noncircular signals compared with traditional blind equalization algorithms.
文摘Some channel compensation techniques integrated into front-end of speech recognizer for improving channel robustness are described. These techniques include cepstral mean normalization, rasta processing and blind equalization. Two standard channel frequency characteristics, G.712 and MIRS, are introduced as channel distortion references and a mandarin digit string recognition task is performed for evaluating and comparing the performance of these different methods. The recognition results show that in G.712 case blind equalization can achieve the best recognition performance while cepstral mean normalization outperforms the other methods in MIRS case which is capable of reaching a word error rate of 3.96%.
文摘A novel Recurrent Neural Network(RNN) based blind equalization algorithm is proposed in the paper.For the first time, the conjugate gradient algorithm and a three point searching method are used in RNN training.Simulation results show that our algorithm is suprior to the one proposed by Kechriotis and the Constant Modulus Algorithm.
基金the National Natural Science Foundation of China (60072001)
文摘A modified constant modulus algorithm (MCMA) for blind channel equalization is proposed by modifying the constant modulus error function. The MCMA is compared with the conventional constant modulus algorithm (CMA) for symbol-spaced equalization of 4PSK signals. The result shows that the performance of the MCMA is superior to that of the CMA in both convergence rate and intersymbol interference for frequency selective channels in noisy environments. Simulation results using 8PSK signals also demonstrate that a fractionally spaced equalizer can preserve performance over variations in symbol-timing phase, whereas a baud-rate equalizer cannot.
基金Supported by the National Basic Research Program of China (Grant No. 2008CB317109)the National Natural Science Foundation of China(Grant No. 60572054)+1 种基金the Foundation of Authors of National Excellent Doctoral Dissertation (Grant No. 200239)the Scientific Research Foundation for Returned Scholars, Ministry of Education of China
文摘We present an adaptive algorithm for blind identification and equalization of single-input multiple-output (SIMO) FIR channels with second-order statistics. We first reformulate the blind channel identification problem into a low-rank matrix approximation solution based on the QR decomposition of the received data matrix. Then, a fast recursive algorithm is developed based on the bi-iterative least squares (Bi-LS) subspace tracking method. The new algorithm requires only a computational complexity of O(md2) at each iteration, or even as low as O(md) if only equalization is necessary, where m is the dimension of the received data vector (or the row rank of channel matrix) and d is the dimension of the signal subspace (or the column rank of channel matrix). To overcome the shortcoming of the back substitution, an inverse QR iteration algorithm for subspace tracking and channel equalization is also developed. The inverse QR iteration algorithm is well suited for the parallel implementation in the systolic array. Simulation results are presented to illustrate the effectiveness of the proposed algorithms for the channel identification and equalization.
文摘In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deconvolution process is carried out with no training symbols and the channel’s coefficients are obviously unknown to the receiver, no actual indication can be given (via the mean square error (MSE) or ISI expression) during the deconvolution process whether the blind adaptive equalizer succeeded to remove the heavy ISI from the transmitted symbols or not. Up to now, the output of a convolution and deconvolution process was mainly investigated from the ISI point of view. In this paper, the output of a convolution and deconvolution process is inspected from the leading digit point of view. Simulation results indicate that for the 4PAM (Pulse Amplitude Modulation) and 16QAM (Quadrature Amplitude Modulation) input case, the number “1” is the leading digit at the output of a convolution and deconvolution process respectively as long as heavy ISI exists. However, this leading digit does not follow exactly Benford’s Law but follows approximately the leading digit (digit 1) of a Gaussian process for independent identically distributed input symbols and a channel with many coefficients.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant No.61374008
文摘Based on the peak to valley ratio(PTVR) of the average magnitude difference function(AMDF), we present a novel optical signal to noise ratio(OSNR) and symbol rate(SR) estimation method for commonly used auxiliary amplitude modulations(AAMs). Moreover, it is demonstrated that the influence of chromatic dispersion(CD)on the method can be mitigated by maximizing the PTVR of the AMDF with additional tunable dispersion compensators. The results of simulations show that the OSNR estimation error can be kept within 0.8 dB in the wide OSNR range of(12, 32) dB, while the SR estimation error is below 0.079% for four widely used10 Gsymbol/s AAM signals.