123 results about "Decision error" patented technology

An apparatus, method and system are provided for correlated noise reduction, in a trellis decoding environment, such as second generation HDSL, in which crosstalk impairments may be significant. The preferred embodiments provide equalization and correlated noise reduction, utilizing a training period to generate corresponding coefficients, and utilizing two different training error signals. In addition, the apparatus method and system also provide continued and adaptive correlated noise reduction during data transmission, utilizing two additional error signals, a trellis error signal and a tentative error signal. The trellis error signal is a decision error of a selected previous state of a selected trellis path, in which the selected trellis path has a smallest cumulative error of a plurality of trellis paths, and the selected previous state is preferably the immediately previous state. The tentative error signal is formed as a difference between a delayed, tentative symbol decision and a delayed received data signal subsequent to equalization, in which the delay is preferably one symbol time. The various embodiments may be utilized with trellis encoding, with or without data precoding.

A system and method is provided overcoming decision-making and communications errors to produce expedited and accurate group choices. The invention provides collective outcomes that are resilient to communication and decision making errors, and which are provided with a minimum wait time. The system comprises a user interface engine that provides a channel to the features of the present invention, an agenda manager module for creating and presenting questions, a user manager module that controls interactions with user who request questionnaires, submit response data, and request access to analytical results, and a report manager module that identifies collective outcomes that are resilient to error and/or that weight individual votes to optimize the group's performance in producing one or more correct or optimal collective choices. A common data exchange allows communication between the modules.

In MIMO wireless communications employing LMMSE receiver, the symbols transmitted through a transmit antenna are estimated at the receiver in the presence of interference consisting of two main components: one due to the additive noise and the other due to (interfering) symbols transmitted via the remaining antennas. This has been shown to hamper the performance of a communication system resulting in incorrect symbol decisions, particularly at low SNR. IMMSE has been devised as a solution to cope with this problem; In IMMSE processing, the symbols sent via each transmit antenna are decoded iteratively. In each stage of processing, the received signal is updated by removing the contribution of symbols detected in the previous iterations. In principle, this reduces the additive interference in which the desired symbols are embedded in. Therefore, the interference level should reduce monotonically as one goes down in processing order. In a noisy environment, however, any incorrect decision made on a symbol in an iteration leaves its contribution in the updated received signal available for processing in the following iterations. Fortunately, if the level of interference is estimated and the soft bits are scaled appropriately by the estimated interference power, the performance of IMMSE receiver can be greatly improved. Preferred embodiments estimate the interference by computing the probability of error in decoding the symbols of the previous stage(s). The computation of decision error probability depends on the constellation size of transmitted symbols and introduces very little processing overhead.

The present invention is related to a decision feedback equalizing apparatus and a method thereof. The object of the invention is to provide to an apparatus and a method of decision feedback equalization that make a channel property of an inferior receiving signal to mild by using a channel-matched filter and decreases decision errors of symbol detector output signals by using a trellis decoder with decreased complexity, whose trace back depth is 1 (TBD=1).

The invention provides a decoding method, a decoding device, and a communication system. Through a mixed mode of soft-decision error correcting coding and hard-decision error correcting coding, multi-grade coding is realized, and through a mixed mode of soft-decesion error correcting decoding and hard-decesion error correcting deconding, multi-grade decoding is realized, the advantages of the two modes are integrated: the system complexity and resource cost are reduced by replacing a multi-grade soft-decision error correcting coding and decoding mode with a primary soft-decesion error correcting coding and decoding mode; other grade hard-decision error correcting coding and decoding are carried out on the basis of the primary soft-decision error correcting coding and decoding, thus the gain performance is guaranteed, and the requirement on gain for a high-speed light transmission system is fulfilled.

The present invention relates to a method for reducing cycle slips in a carrier recovery loop for a phase detector, the method comprising the steps of receiving an input signal consisting of samples, each received sample having an in-phase (I) and quadrature-phase (Q) component, providing the input signal to a phase error estimator adapted to determine a phase error estimate, providing the phase error estimate to a loop filter, and forming an output signal from the carrier recovery loop by subtracting an output from the loop filter from the input signal, wherein the phase error estimate is determined based on a combination of the amplitude and phase of the samples and a probability measure for a specifically transmitted symbol, thereby improving phase tracking performance of the carrier recovery loop.

Advantages with the present invention includes reduction of cycle slips without using a high performance, and expensive, hardware solution, at the same time as it is possible to suppress the effects of decision errors which enables higher gain, thereby giving an improvement in Bit Error Rate (BER) in low SNR conditions.

The present invention also relates to a corresponding phase detector

The soft decision thresholds in a soft decision forward error correction (FEC) system may be adjusted based on mutual information of a detected signal. In one embodiment, a recursive algorithm may be used to optimize threshold values by maximizing the mutual information. In another embodiment, an adaptive scheme may be used to optimize threshold values based on a pre-knowledge of the noise in the channel. In a further embodiment, an adaptive scheme may be used to optimize threshold values by without pre-knowledge of the noise in the channel.

The invention discloses a distributed media access control protocol, in particular to a proxy polling mixed access protocol for increasing the capacity of a wireless local area network. The invention designs an access strategy based on polling to avoid channel conflicts, namely, according to a partial schedule strategy designed by the protocol, the existing transmission traffic flow substitutes an AP to select next transmission traffic flow, which leads the traffic flow in a network to be transmitted in sequence in a relay way. Meanwhile, the protocol adopts an access strategy based on competition as supplement to solve problems arising when a polling decision is wrong. The partial schedule strategy of the invention provides a service differentiating system based on conditions, which promotes the fairness of services with low priority when network load is relatively low. On the basis of a strategy for forecasting queue information, the partial schedule strategy further adopts a periodic polling strategy as supplement to modify wrong polling decisions on time, so as to adapt to service arrival models. The protocol remarkably increases the capacity of networks and has good performance.

The application discloses a high-reliability error detection method for a storage, a reading control method and device. The high-reliability error detection method comprises the following steps of: applying a preset detection voltage on a storage unit of the storage, wherein the detection voltage is the sum of a default voltage and a bias voltage; obtaining a voltage level of the storage unit; comparing the voltage level of the storage unit with a reference voltage to obtain storage data; adopting a first LLR (Logarithmic Likelihood Ratio) to carry out first soft-decision decoding of LDPC (LowDensity Parity Check) on the storage data; the method also comprises the steps of: adopting hard-decision decoding of the LDPC to carry out high-reliability error detection, and when judging the occurrence of high-reliability error, adopting a second LLR to carry out second soft-decision decoding on the storage data. The new high-reliability error detection method provided by the method has the advantage that when the high-reliability errors occur, the redistribution of the LLR is adopted to reduce the damage for the soft-decision error correcting capability.

Disclosed is a receiving device which comprises first and second AD converters for inputting a received analog signal and converting the analog signal to digital signals in response to sampling clock signals of mutually different phases, first and second adaptive equalizers for respectively receiving outputs of the first and second AD converters, third and fourth adaptive equalizers for respectively receiving outputs of the second and first AD converters, a first adder for adding the outputs of the first and second adaptive converters, a second adder for adding the outputs of the third and fourth adaptive equalizers, a first decision unit for receiving the output of the first adder, deciding a received symbol for output, and outputting a decision error, a second decision unit for receiving the output of the second adder, deciding a received symbol for output, and outputting a decision error, and a multiplexing circuit for multiplexing the received symbols output from the first and second decision units, for output. The decision error from the first decision unit is supplied to the first and second adaptive equalizers, and the decision error from the second decision unit is supplied to the third and fourth adaptive equalizers.

The invention discloses a corrected mold decision multi-mode blind equalization method MMDMMA. The method comprises the following steps: re-defining a cost function, and acquiring a weight vector update formula of a forward equalizer and a feedback filter through the defined cost function according to a stochastic gradient descent method; replacing a fixed decision factor of the conventional mold decision multi-mold blind equalization method MMDMMA by using a leakage factor with time-variant characteristics, so that a time-varying signal can be accurately tracked. The replacement has the effects that a decision error is large, a time-varying leakage factor is large, and a convergence rate is high before convergence; the decision error is small, the time-varying leakage factor is small, and the convergence rate is low after the convergence; due to the adoption of the time-varying leakage factor, divergence of the blind equalization process in the MDMMA method is avoided, and misadjustment is avoided. The method is low in mean square error, high in convergence speed, and high in capacities of inhibiting intersymbol interference and correcting phase rotation. Compared with a mold decision multi-mode blind equalization method MDMMA and a norm blind equalization method CMA, the method MMDMMA is obviously improved.

An equalization method and device for equalizing the received vestigial sideband (VSB) signal, utilizes segment-sync symbols, Sato directions, erasure slicers, and variable step-sizes. In addition to stop-and-go (SAG) mode, the directions of Sato errors can also be used for speed up the convergence of tap weights of the equalizer. Erasure slicers can mitigate the effect of decision errors as they are passed through the feedback filter. In time-variant environments, variable step-sizes help the equalizer tracking the variations of the channels; in time-invariant environments, variable step-sizes help ease the fluctuations of the steady-state equalizer tap weights, and therefore yield smaller mean-squared-error and better symbol error rate (SER).

To obtain excellent reception performance whilst cutting down the amount of computing operation in a MIMO communication system using soft-decision error correction coding. Received waves picked up by receiving antennas 401-1 to 401-R are converted from the radio frequency to the baseband signal by respective receivers 402-1 to 402-R to be output as a received signal. A signal detector 403 calculates bit LLRs of the transmitted signal based on the received signal and the channel-estimated values obtained from a channel estimator 404. The bit LLRs output from signal detector 403 are rearranged by deinterleaver units 405-1 to 405-T in the patterns opposite to the patterns in which interleaving was performed on the transmission side. The bit LLRs after de-interleaving are subjected to an error correction decoding process through decoders 406-1 to 406-T. The bit sequences after decoding are parallel-to-serial converted by a parallel-to-serial converter 407 so that the detected transmission bit sequence is output.

An assignment scheme exploits the Media Access Control (MAC) layer protocol features under various MAC layer call scenarios. In one embodiment, the Hamming distance between pairs of critical Data Units are assigned to codewords with a minimum distance of dmin2=8 bits, thereby increasing the hard decision error correcting capability from 1 bit to 3 bits when deciding between these pairs of Data Units. The method for assigning data unit identification (DUID) codes by a radio operating within a wireless communication system includes determining by the radio whether an expected burst is a 4 Voice Burst with Encryption Synchronization Signaling (4V); when the expected burst is 4V, decoding the DUID within the received burst using an increased minimum distance; and when the expected burst is not 4V, decoding the DUID within the received burst using a minimum distance.

The invention relates to an anti-interference method for the phase tracking of a digital signal receiver and a device thereof. The traditional phase tracking method can result in decision error when a narrow band interference signal is overlapped in a signal channel band. The method of the invention is that a pseudorandom sequence Ri generated by a receiver is taken as a rotation control variable; symbol scrambling is imposed on a current constellation according to the pseudorandom sequence Ri; phase identification is carried out to the constellation after the symbol scrambling and loop filtering is carried out to the output of the phase identification; the control variable after the loop filtering is used for controlling the phase shift degree and compensating the phase of the constellation. The device of the invention comprises a phase shifter, a phase identifier, a loop filter, a pseudorandom sequence generator and a symbol scrambler. The anti-interference method of the invention achieves the aim of anti-interference by the symbol scrambling to eliminate the relativity of the narrow band interference going into the band with strong time relativity. The method enhances the stability of a phase tracking loop and ensures the receiving performance of a digital receiving system.

An operation method of a memory controller includes: reading a second data from memory cells when a hard decision error correction decoding operation based on a first data read from the memory cells fails; calculating a LLR of each bit-data included in the first data by using the first and second data; and performing a soft decision error correction decoding operation based on the LLR, wherein the memory cells include a first and second memory cell, wherein the first data includes first-bit-data read from the first and second memory cell, wherein the second data includes second-bit-data read from the first and second memory cell, wherein the LLR is a LLR of the first-bit-data read from the first memory cell calculated based on the first bit and a second bit read from the first memory cell and a first bit and a second bit read from the second memory cell.

The invention provides a power grid investment measurement and calculation method and system based on grey relational analysis and a medium, and the method comprises the steps: an alternative index set obtaining step: collecting external factors affecting the power demands from the aspects of macroeconomy, industrial structures and the output values of all industries, and forming the alternative index set; and a correlation degree analysis step: performing correlation degree analysis on the obtained alternative index set, and extracting an index which is greatly correlated with the annual income increasing electric quantity index of the company from the alternative index set as a key external influence factor. According to the invention, a gray correlation analysis method is adopted to extract key political and economic indexes of power grid investment; and power grid investment prediction is carried out by adopting multiple linear regression according to the extracted key factor quantitative indexes, so that decision errors caused by ignoring political economic and environmental changes only by virtue of a time sequence are avoided, and the proposed prediction method has very strong guidance and universality for different provincial companies.

The invention relates to a method for classifying electroencephalogram (EEG) signals based on a multi-scale brain function network. The method comprises the steps that data are acquired, specifically,the EEG signals in a resting state are collected and preprocessed; multi-scale time series are calculated, specifically, multi-scale processing is conducted on preprocessed time series of all leads,and thus the generalized multi-scale coarse-grained time series are obtained; the multi-scale brain function network is built, specifically, the amplitude correlation degree and the phase correlationdegree of all the leads of the EEG signals are taken as the quantitative standards to calculate multi-scale weighted brain function networks; a multi-scale convolutional neural network capable of learning the multi-scale brain function network is built; and neural network training is conducted, specifically, the cross-correlation degree of decision errors generated by all convolutional neural network paths is taken as a penalty term and a penalty loss function to accelerate decision-making of the neural network and reduce the generalization error.