55 results about "Blind equalizer" patented technology

A single-axis receiver processing, for example, complex vestigial sideband modulated signals with an equalizer with forward and feedback filters. Forward and feedback filters have parameters that are initialized and adapted to steady state operation. Adaptive equalization employs linear predictive filtering and error term generation based on various cost criteria. Adaptive equalization includes recursive update of parameters for forward and feedback filtering as operation changes between linear and decision-feedback equalization of either single or multi-channel signals. An adaptive, linear predictive filter generates real-valued parameters that are employed to set the parameters of the feedback filter. In an initialization mode, filter parameters are set via a linear prediction filter to approximate the inverse of the channel's impulse/frequency response and a constant modulus error term for adaptation of the filter parameters. In an acquisition mode, equalization is as linear equalization with a constant modulus error term, and possibly other error terms in combination, for adaptation of the filter parameters. In a tracking mode, equalization is as decision feedback equalization with decision-directed error terms for adaptation of the filter parameters. For some equalizer configurations, feedback filtering is applied to real-valued decisions corresponding to complex-valued received data, and includes real-part extraction of the error term employed for recursive update of filtering parameters. Where a training sequence is available to the receiver, initial parameters for forward filtering are estimated by correlation of the received signal with the training sequence.

A method and system for measuring noise and or interference in a communications signal without taking the signal out of service. In the present invention the communications signal is converted from an RF signal into an IF signal. The IF signal is then digitized and stored. The stored signal is processed to determine the interference signal. The interference signal is calculated from an error vector produced by a blind equalizer demodulator. The interference signal is extracted and presented to a user.

In Software defined elastic optical networks, modulation format and constellation size may be flexibly modified. As a result, digital signal processing (DSP) algorithm should be compatible with different modulation schemes or readily reconfigurable at the optical coherent receiver. Therefore we propose a novel cascaded adaptive blind equalizers based on decision-directed modified least mean square (DD-MLMS) algorithm for polarization separation and carrier phase recovery. The algorithm is square quadrature amplitude modulation (QAM) independent so that it could be applied in the elastic optical systems. The 28 Gbaud polarization multiplexing quadrature phase shift keying (PM-QPSK) and PM-16QAM back-to-back transmission is demonstrated. The results show that the performance is very close to the general algorithm but with a benefit of the reduced operation complexity. We transmit the 8×240 Gb/s PM-16QAM wavelength division multiplexing (WDM) signal over 1200 km standard single mode fiber (SSMF) based on the proposed blind equalization with a bit error ratio (BER) less than 2×10−2.

Methods and apparatuses for blind equalizers with multiple constant modules. In one embodiment, a circuit, includes: a filter to produce an output based on an input that represents a symbol being received, the symbol being one of a Quadrature Amplitude Modulation (QAM) constellation; a decision engine coupled to the filter to generate a result indicating one region of a plurality of regions in a QAM constellation diagram, the output of the filter being in the indicated region which includes a plurality of symbols of different radii in the constellation diagram; and an error reduction engine coupled to the decision engine and the filter to reduce a difference between a selected one of a plurality of constants and a modulus of the output; where each of the plurality of constants correspond to one of the plurality of regions; and the selected one of the plurality of constants is selected according to the result of the decision engine.

The embodiment of the invention relates to the technical field of communication and particularly discloses a method, a device and a decoder for blind equalization in order to solve the problems that the prior art for blind equalization has difficulties in convergence and has poor equalization effect after the convergence. The method in the embodiment of the invention comprises the following steps: equalizing the received symbol sequences; carrying out the demodulating and decoding processes on the equalized symbol sequences, to generate decoded signals; carrying out the CRC (cyclic redundancy check) on the decoded signals; if errors are detected according to the CRC, re-demodulating the decoded signals and updating the equalization coefficient according to the re-demodulated signals; and re-equalizing the received symbol sequences. By modulating the output of the decoder and feeding back to a blind equalizer to update the coefficient of the blind equalizer and by carrying out the iteration method using the decoded signals for multiple times to produce the gain, the embodiment of the invention can reduce the probability of errors in judgment, ensure that the equalizer can achieve the convergence rapidly, enhance the equalization effect of the equalizer and improve the performance of the receiver.

The invention provides a blind equalizer and a blind equalization processing method, which are suitable for the field of communication. The blind equalizer comprises a weight updating unit and a wave filter, wherein the weight updating unit comprises a first weight updating module, a second weight updating module and a weight merging module. In the blind equalizer and the blind equalization processing method, a weight vector is updated by making the error items of the first weight updating module minimum and making the logarithmic value of a local posterior probability density function adopted by the second weight updating module maximum, and a received signal vector is output after the received signal vector is subjected to the equalization processing according to the updated weight vector, so the blind equalizer which can increase velocity of convergence and improve steady-state performance is implemented.

The invention discloses a blind equalization method with the integration of orthogonal wavelet transformation and time diversity technique. Integrated with time diversity technique, wavelet transformation technique, phase-lock ring technique and decision-directed (DD) algorithm, the blind equalization method can reduce the influences of multipath effect by using time diversity, can overcome the disadvantages of asymmetry of constant modulus error function by using a hyperbolic tangent error function, can lower the self-correlativity of input signals of a blind equalizer by using orthogonal wavelet transformation to improve the convergence speed, can reduce stable error by using DD algorithm, and can correct phase rotation by using digital phase-lock ring technique. The method has the advantages of high convergence speed and less mean square error, and can effectively suppress phase rotation.

The present invention relates to blind decision feedback equalization. The present invention selects one of a filter signal and a quantized signal as an input signal of a feedback filter in the DFE and update the tap coefficient according to the SAG flag f[k] by including a main filtering unit, a SAG flag determining unit and a blind feedback controlling unit. The present invention prevents decrement of a performance caused by an error propagation and also improve a convergence performance in an equalization apparatus and reduce a symbol error rate (SER) at a steady state after converging. In conclusion, the present invention can be used effectively to a receiver in a digital TV, which is required the blind equalizer.

The invention discloses a combination optimization self-adaptive frequency domain blind equalization method and a system for achieving the method. Through combination of two frequency domain equalizers of two different types, automatic switching of two work modes can be achieved without error threshold selection; in the frequency domain blind equalization work mode, when the equalization beginning stage or channels suddenly change, intersymbol interference is eliminated; when the frequency domain blind equalization work mode obtains steady-state mean square error which is low enough, a frequency domain judging guiding mode is switched to. Combination output is obtained by combining the output of the two equalizers through combination parameters, the combination output is used for defining a time domain cost function of the whole combination optimization self-adaptive frequency domain blind equalization system to adjust the combination parameters; judging output of the combination output is used for adjusting the equalization performance of the frequency domain self-adaptive equalizers. Compared with a single frequency domain multi-mode blind equalizer and a single frequency domain self-adaptive equalizer, the method and system have good real-time tracking performance, the convergence rate is high, steady-state errors are low, and calculation complexity is greatly lowered.

The invention provides an adaptive blind equalization method based on deviation compensation, and belongs to the technical field of broadband wireless digital communication blind equalization. The adaptive blind equalization method comprises noise variance estimation, blind channel identification deviation compensation, equalizer construction and blind restoration, and comprises the following steps: 1, performing over sampling on received signals at a receiving end to obtain two paths of received signal sequences; 2, estimating transmission channel properties to obtain a biased estimation value of the transmission channel properties; 3, calculating an estimation deviation of the biased estimation value of the transmission channel properties; 4, compensating the biased estimation value to obtain a compensated biased estimation value of the transmission channel properties; 5, constructing an equalizer; 6, constructing a received signal vector, and performing blind restoration on an input signal sequence; and 7, judging whether a cycle counting value reaches the maximum value, and deciding whether the method is accomplished. By adoption of the method, unknown additive noise variances can be estimated in real time, more accurate estimation of the transmission channel properties is obtained, the convergence performance is excellent, and the output precision of the blind equalizer and the anti-interference ability of the system are improved.

The invention discloses a blind equalization method for a wavelet neural network based on space diversity. On the basis of analysis of a space diversity technology and the equalization performance of a wavelet neural network, the method reduces the influence of fading by utilizing the space diversity and overcomes intersymobl interferences by using the stronger approximation capacity of a blind equalizer of the wavelet neural network. The invention overcomes the intersymobl interferences caused by the multipath propagation and the fading characteristic of a channel at a receiving end, improves the communication quality and has high convergence speed and small mean square error. The effectiveness of the method is verified by an acoustic channel simulation result. The method can effectivelyrealize the separation of signals and noise and the real-time restoration of the signals.

The invention discloses a wavelet constant modulus blind equalization method in a MIMO (Multiple Input Multiple Output) system from the aspect of reducing?inter channel?and inter signal?correlation, so as to overcome defects that the traditional constant modulus blind equalization method in the MIMO system is weak in inter channel interference inhibition ability, slow in the convergence rate and large in steady-state errors. According to the method, singular value decomposition is used for reducing the correlation of channel output signals; an orthogonal wavelet base function is used for carrying out orthogonal wavelet transformation on MIMO channel output signals and autocorrelation of input signals of a blind equalizer is reduced; on the basis of fully considering the inter channel correlation, a cost function of MIMO system constant modulus blind equalization algorithm is redefined, and cross-correlation of output signals of the blind equalizer is reduced; and a variable step size function is used for controlling a blind equalization?weight vector?updating process, the convergence rate quickened, and the steady-state errors are reduced.

The invention discloses a wavelet multimode blind equalization method introducing an immune-optimized SVM (Support Vector Machine). Based on the global searching capability of an immune clonal selection algorithm, parameter selection in an SVM blind equalization method is changed from manual selection into automatic determination, and then, the SVM is introduced into an orthogonal wavelet multimode blind equalization method, so that the wavelet multimode blind equalization method introducing the immune-optimized SVM is invented. The method comprises the following steps of: training a small segment of extracted initial data through the SVM to estimate the initial weight value of a blind equalizer, simultaneously, executing optimum selection for the parameters in the SVM by use of an immune algorithm, and taking the initial weight value estimated through the SVM as a weight vector of the orthogonal wavelet multimode blind equalization method. Compared with a multimode blind equalization method, the orthogonal wavelet multimode blind equalization method and an SVM orthogonal wavelet multimode blind equalization method, the method provided by the invention has the advantages of high convergence rate and small steady-state error, and can be used for improving the quality of underwater sound communication better.

The invention provides an equilibrium method of communication signals of an underwater acoustic channel. Orthogonal WT is utilized to perform preprocessing on an input signal of an equalizer to reduce the signal to noise ratio of the signal, a CS algorithm with excellent global searching ability is introduced into an MMA and utilized to optimize a cost function of the MMA to obtain global optimal solution of an initial weight vector of the blind equalizer, and accordingly, equilibrium quality of the communication signals of the underwater acoustic channel is improved comprehensively. The equilibrium method of the communication signals of the underwater acoustic channel has the advantages of capturing the global optimal solution well, effectively solving the problems that the MMA is likely to be caught in local minimum, low in convergence rate, large in steady state error and the like, and being high in convergence rate, few in mean square error and high in equilibrium quality.

The invention discloses a method for assisting deep learning based on blind equalization, which belongs to the field of communication and comprises the following steps: sampling: sampling a received modulation signal, and sending the sampled signal to a blind equalizer; equalization: equalizing the received signal by using multiple step lengths; checking and clearing: checking the equalized signaldata, and clearing the empty data which fails to be equalized; and identification learning: sending all successfully equalized data to a deep learning network, extracting implicit information in thedata, and identifying equalized signals by utilizing the implicit information. The invention further discloses a system based on the method, the system comprises an equalization module and a deep learning module, and the equalization module and the deep learning module bidirectionally form a transmission link. The method has the advantages that the received signals are equalized by using a blind equalization method, and then the potential information is acquired by using the deep learning network for identification, so that the identification accuracy of unknown signals is improved.

A method for synchronizing symbols at the output of a blind equalizer, the method being characterized by the following steps: on sending, inserting into a succession of sent symbols, one or more known sequences of symbols repeated in said succession of symbols; detecting said one or more known sequences at the output of said blind equalizer; deducing any shifting of the symbols at the output of the blind equalizer from the result of said detection; and retiming the symbols at the output of the blind equalizer as a function of the deduced shift.

The invention relates to a blind equalizer of a multi-carrier receiving device, which comprises a removing unit for the additional data, an FFT unit, a self-adapting equalizing unit, and an error calculating unit; wherein, the removing unit for the additional unit is used to remove the additional data from the multi-carrier signal received, retain only the effective data, and add the additional data into the signal for transmission and reception; the FFT unit is used to calculate the filed effective data to convert the same into frequency domain signals; the self- adapting equalizing unit is intended for equalizing the converted signals based on a predefined mathematical expression; the error calculating unit is used to calculate the errors in the equalized signals received. The self-adopting unit is able to update the predefined mathematical expression by means of the calculated errors. Therefore, the blind equalizer has an advantage of even compensating the channel changing instantaneously.

The invention discloses an improved T/2 fractional spaced coordinate transforming blind equalization method (T/2-FSE-RCTCMA). Aiming at the defects of low convergence speed and large remainder error of a fractional spaced blind equalization method (T/2-FSE-CMA) during equalizing a higher order QAM signal, the improved method adopts the following steps: separately equalizing a real part and an imaginary part of an input signal of a fractional spaced blind equalizer by analyzing the distribution characteristic of a 16QAM signal constellation diagram; transforming output signals onto the same circle by utilizing coordinate transformation so as to obtain a constant modulus error function after the coordinate transformation; and using the error function to adjust weight vectors of each path of blind equalizers of the T/2 fractional spaced blind equalizer. The improved method effectively overcomes erroneous judgments of the T/2 FSE CMA method to multi-modulus higher order QAM signals during equalizing. The T/2-FSE-RCTCMA method has high convergence speed and small mean square error.

The invention provides an underwater blind equalization system, comprising a blind equalizer. The underwater blind equalization system is characterized by further comprising an underwater independent component analysis subsystem which is a preprocessing part of the blind equalization system, wherein the independent component analysis subsystem introduces different channel characteristic functions and Gaussian white noise as well as judgment logic and is used for carrying out judgment on a separation signal so as to separate the noise from a source signal; and an output signal of the independent component analysis subsystem is an input signal of the blind equalizer. A blind equalization method combined with independent component analysis comprises the following steps of: carrying out improvement on the traditional independent component analysis model so as to lead the traditional independent component analysis model to be applicable to an underwater sound communication system, using an underwater independent component analysis technology at the front end of the blind equalizer as the preprocessing part of the equalizer and forming a new blind equalization method. Compared with the traditional blind equalizer, the blind equalizer provided by the invention has the advantage that a signal constellation diagram output by the new method is clearest and most compact.

The invention discloses a blind equalization and image blind restoration method based on DNA (DeoxyriboNucleic Acid) glowworm swarm optimization. The method comprises the following steps that: firstly, utilizing a DNA genetic method to optimize a glowworm population to obtain a DNA glowworm optimization method; then, combining the obtained DNA glowworm optimization method with the image blind restoration method; and taking the global search ability of the DNA glowworm optimization method to optimize the initial weight vector of a blind equalizer, and taking the initial weight vector obtained by optimization as an initial point for updating a blind equalizer weight vector. Update is carried out by taking a blind equalizer weight vector update method, and an image blind restoration effect is improved. In addition, in an image blind restoration process, an image does not need to be subjected to dimension reduction and dimension rising processing, information loss is reduced, an image restoration effect is better, and the method has a high practical value in the technical field of communication.

The invention relates to an electromagnetic leakage signal recovery-enhancement method and system. The method comprises that an electromagnetic leakage signal model including environment noises and wireless channel noises is established according to characteristics of the environment and wireless channel noises; according to the electromagnetic leakage signal model, an electrical leakage signal is divided into a high-frequency electromagnetic leakage signal portion and a low-frequency electromagnetic leakage signal portion, and self-adaptive inverse filtering is carried out on the high-frequency electromagnetic leakage signal portion and the low-frequency electromagnetic leakage signal portion; and the high-frequency electromagnetic leakage signal portion and the low-frequency electromagnetic leakage signal portion pass blind equalizers thereof to obtain output signals respectively, and the two output signals are combined in the convex combination manner to obtain an electromagnetic leakage signal recovery and enhancement model. The recovery-enhancement method can be used to effectively recover and enhance received video signals according to the physical characteristics of the electromagnetic leakage signal so that the video signals is high in the understandability, and the attack capability of TEMPEST is improved.