1174 results about "Log likelihood" patented technology

The invention discloses a density evolution based polarization code constructing method and polarization code coding and decoding system. According to the invention, the code length N and the information bit length K of an information code to be processed are obtained, an expectation value set of a log-likelihood ratio probability density function of N bit channels, K bit channels are selected as the information bit channels according to the expectation value set and information bit information index vector quantity is generated; an information bit sequence and a fixed bit sequence are mixed and the mixed bit vector quantity is multiplied by a polarization code for generating a matrix so as to output an encoding sequence; the encoding sequence is modulated and input into a transmission channel and the sequence output by the transmission channel is subjected to decoding operation by adopting a polarization code decoding algorithm, bit error probability and frame error rate of the decoded code are calculated and a design signal to noise ratio is changed, the above operation is repeated until the bit error probability and frame error rate become the minimum. The method and system provided by the invention are suitable for general binary system memoryless channels, the bit error probability and frame error rate are low, the calculation complexity is low and the communication performance of a communication system is improved.

Methods and apparatus are provided for measuring the performance of a read channel. A number of detection techniques, such as SOVA and maximum-a-posteriori (MAP) detectors, produce a bit decision and a corresponding reliability value associated with the bit decision. The reliability value associated with the bit decision may be expressed, for example, in the form of log likelihood ratios (LLRs). The reliability value can be monitored and used as a performance measure. The present invention provides a channel performance measure that generally correlates directly to the BER but can be collected in less time.

Data stored in non-volatile storage is decoded using iterative probabilistic decoding and multiple read operations to achieve greater reliability. An error correcting code such as a low density parity check code may be used. In one approach, initial reliability metrics, such as logarithmic likelihood ratios, are used in decoding read data of a set of non-volatile storage element. The decoding attempts to converge by adjusting the reliability metrics for bits in code words which represent the sensed state. If convergence does not occur, e.g., within a set time period, the state of the non-volatile storage element is sensed again, current values of the reliability metrics in the decoder are adjusted, and the decoding again attempts to converge. In another approach, the initial reliability metrics are based on multiple reads. Tables which store the reliability metrics and adjustments based on the sensed states can be prepared before decoding occurs.

Methods and apparatus are provided for high-speed, low-power, high-performance channel detection. A soft output channel detector is provided that operates at a rate of 1 / N and detects N bits per 1 / N-rate clock cycle. The channel detector comprises a plurality, D, of MAP detectors operating in parallel, wherein each of the MAP detectors generates N / D log-likelihood ratio values per 1 / N-rate clock cycle and wherein at least one of the plurality of MAP detectors constrains each of the bits. The log-likelihood ratio values can be merged to form an output sequence. A single MAP detector is also provided that comprises a forward detector for calculating forward state metrics; a backward detector for calculating backward state metrics; and a current branch detector for calculating a current branch metric, wherein at least two of the forward detector, the backward detector and the current branch detector employ different trellis structures.

An efficient telecommunications receiver system for accurately decoding a received composite signal having a data signal component and a pilot signal component. The receiver system includes a first circuit for receiving the composite signal and extracting a pilot signal and a data signal from received composite signal. A second circuit calculates a log-likelihood ratio as a function of a channel estimate based on the pilot signal. A third circuit scales the log-likelihood ratio by a predetermined log-likelihood ratio scaling factor and provides an accurate log-likelihood value in response thereto. A fourth circuit decodes the received composite signal based on the accurate log-likelihood value and the data signal. In a specific embodiment, the pilot signal and the data signal comprise pilot samples and data samples, respectively. The third circuit includes a carrier signal-to-interference ratio circuit for computing a first signal-to-interference ratio and a second signal-to-interference ratio based partly on the pilot signal. The first signal-to-interference ratio is based on the data samples, and the second signal-to-interference ratio is based on the pilot samples. The first signal-to-noise ratio and the second signal-to-noise ratio provide input to a circuit for computing the predetermined log-likelihood ratio scaling factor that is included in the third circuit. In a more specific embodiment, the first circuit includes a despreader for despreading the received composite signal in accordance with a predetermined spreading function and providing a despread signal in response thereto. The spreading function is a pseudo noise sequence or a Walsh function. The first circuit further includes a decovering circuit that extracts the pilot signal and the data signal from the despread signal. In the illustrative embodiment, the accurate receiver system further includes a circuit for generating a rate and / or power control message and transmitting the rate and / or power control message to an external transceiver in communication with the efficient receiver system.

An integrated maximum a posteriori equalization and turbo product coding (IMAP-TPC) system for optical fiber communications systems (OFCS) is provided that uses probabilistic characterization of the electrical current in the presence of inter-symbol interference (ISI) and noise to compensate their effects and improve the bit error rate. In the IMAP-TPC system, turbo product code (TPC) decoding is integrated with a symbol-by-symbol maximum a posteriori (MAP) detector. The MAP detector calculates the log-likelihood ratio of a received symbol using the conditional electrical probability density information, and hence obtains a much more accurate reliability measure than the traditional measure used in the TPC decoder.

Symbol by symbol MAP detection for signals corrupted by colored and / or signal dependent noise. A novel means is presented for recursive calculation of forward metrics (α), backward metrics (β), and corresponding soft information (e.g., which can be provided as LLRs (log likelihood ratios)) within communication systems in which a trellis can be employed to perform demodulation of a received signal sequence. For signals that have been corrupted by colored and / or signal dependent noise, this means provides for the ability to perform novel soft information calculation for subsequent use in iterative decoding processing. Many types of communication channels can benefit from this novel means of detection including communication channels within hard disk drives (HDDs).

A novel and useful apparatus for and method of multiple input multiple output (MIMO) detection for use in MIMO based communication systems. The mechanism of the invention performs a simplified tree search utilizing a single stage expansion of the most likely first symbol candidates, in the case of a 2×2 MIMO system. The invention also provides a refinement mechanism that is operative to significantly improve the soft information (i.e. log likelihood ratio) of the list of candidates. To improve the soft information, the mechanism applies one or more refinements rounds to generate additional candidates for both first and second detected symbols.

An iterative method (400) and apparatus (200) for a receiver for reducing interference in a desired signal in a GSM communication system uses a finite-impulse-response filter combined with alternate quadrature component output selection for alternate linear equalization are disclosed The method includes inputting a burst of data of a received waveform including interference, training an alternate linear output filter with a midamble of known quadrature phase, providing an estimate of the desired signal by operating on the received waveform with the finite-impulse-response filter, generating log likelihood ratio estimates for a plurality of bits in the burst of data, selecting bits from the burst of data base upon a predetermined condition, and re-training the alternate linear output filter to provide a second improved estimate of the desired signal.

An impluse response hmn(q) of each transmission path is estimated from N received signals rm (m=1, . . . , M) and a known signal (for a number of users equal to N, n=1, . . . , N). M×N matrix H (q) having hmn(q) as an element and a Q×Q matrix H having H(q) as an element are determined (where Q represents a number of multipaths of each transmitted wave and q=0, . . . , Q−1). A soft decision value b′n(k) is determined from decoded λ2 [bn(k)], and this is used to generate an interference component matrix B′(k) to generate an interference replica H·B′(k). The interference replica H·B′(k) is subtracted from a received matrix y(k) to determine y′(k). y(k) and H are used to determine an adaptive filter coefficient wn(k) to be applied to an n-th user in order to eliminate residual interference components in y′(k) according to the minimum mean square error criteria. y(k) is passed through wn(k) to provide a log-likelihood ratio as a received signal from the user n from which interferences are eliminated.

A method and apparatus to adaptively puncture bits within QAM modulated data symbols transmitted in a communication system in order to effect a signaling channel. The method and apparatus utilize inherent characteristics of a particular mapping scheme for the QAM constellation to selectively puncture particular bits within a data symbol with signaling information and predetermined binary values to selectively increase the log-likelihood ratio gains of those particular bits punctured with the signaling information. The log-likelihood ratios are used to obtain the signaling information and, thus, increasing the gain of the log-likelihood ratios affords greater reliability for the signaling information without increasing the required system resources.

A novel and useful apparatus for and method of multiple input multiple output (MIMO) detection for use in MIMO based communication systems. The mechanism of the invention performs a simplified tree search utilizing a single stage expansion of the most likely first symbol candidates, in the case of a 2×2 MIMO system. The invention also provides a refinement mechanism that is operative to significantly improve the log likelihood (LLR) of the list of candidates. To improve the LLR, the mechanism applies refinements rounds to generate additional candidates for both first and second detected symbols.

A system for providing an accurate interference value signal received over a channel and transmitted by an external transceiver. The system includes a first receiver section for receiving the signal, which has a desired signal component and an interference component. A signal extracting circuit extracts an estimate of the desired signal component from the received signal. A noise estimation circuit provides the accurate interference value based on the estimate of the desired signal component and the received signal. A look-up table transforms the accurate noise and / or interference value to a normalization factor. A carrier signal-to interference ratio circuit employs the normalization factor and the received signal to compute an accurate carrier signal-to-interference ratio estimate. Path-combining circuitry generates optimal path-combining weights based on the received signal and the normalization factor. In the illustrative embodiment, the system further includes a circuit for employing the accurate interference value to compute a carrier signal-to-interference ratio. An optimal path-combining circuit computes optimal path-combining weights for multiple signal paths comprising the signal using the accurate interference value and provides optimally combined signal paths in response thereto. A log-likelihood ratio circuit computes a log-likelihood value based on the carrier signal-to-interference ratio and the optimally combined signal paths. A decoder decodes the received signal using the log-likelihood value. An additional circuit generates a rate and / or power control message and transmits the rate and / or power control message to the external transceiver.

A data reading method adapted to a rewritable non-volatility memory module having physical blocks is provided, wherein each physical block has a plurality of physical pages. In the data reading method, each physical page is partitioned into bit data areas, where at least one of the bit data areas has a data length different from that of the other bit data areas. Data is written into the bit data areas. Data in each bit data area is corresponding to an ECC frame. The data is read from the bit data areas. Because the at least one of bit data areas has a relatively short data length, the error correction capability is improved and the data can be correctly read. An error bit information is obtained according to the read data. A log likelihood ratio (LLR) lookup table or a threshold voltage is adjusted according to the error bit information.

An apparatus and method are provided for normalizing input soft metric to a channel decoder in a wireless communication system. A demapper generates soft metric using an in-phase component (Xk) and a quadrature component (Yk) of a received modulated symbol (Rk), a channel fading coefficient (gk) and a constant value (c) defined by a modulation order of the received modulated symbol. A normalizer receives the soft metric, computes a normalized log likelihood ratio (LLR) by multiplying the soft metric by a ratio of the constant value to a noise variance value, transforms the normalized LLR into a desired range and a desired number of bits, and outputs an input LLR of the channel decoder.

The present invention is intended to provide an LDPC coding scheme which is capable of efficiently implementing a high-performance and high-speed encoder and decoder of an error correcting code suitable for the field of communications such as mobile communications. As to the configuration, a Tanner graph for representing codes with variable nodes and check nodes is used to classify the individual nodes into a plurality of categories. For calculating a probability propagation in iterative decoding, weighting previously determined for each category is performed on a log-likelihood ratio (LLR) subjected to propagation.

A system and method detect symbols of a modulated signal received via a plurality of channels of a wireless communications system. A symbol transmitted via the channels is initially estimated based on the channel estimate from either pilot symbol or previously estimated symbol, and then channel estimate is updated. The next estimate of the symbol is computed by using updated channel information and maximizing the expectation of the log likelihood function. The next estimate is then quantized according to the signal constellation. The quantized estimate of the symbol is compared with the previous estimate of the symbol to determine if the previous estimate of the symbol and the quantized next estimate of the symbol have converged. Otherwise, the quantized next estimate of the symbol is made as the input for the next iteration, and the updating, optimizing, quantizing, and comparing are repeated until the estimate converges.

Data stored in non-volatile storage is decoded using iterative probabilistic decoding. An error correcting code such as a low density parity check code may be used. In one approach, initial reliability metrics, such as logarithmic likelihood ratios, are used in decoding sensed states of a set of non-volatile storage elements. The decoding attempts to converge by adjusting the reliability metrics for bits in code words which represent the sensed state. Simulated annealing using an adjustable temperature parameter based on a level of error in the data read from the system can be performed to assist the iterative decoding process. The simulated annealing can introduce randomness, as noise for example, into the metric based decoding process. Moreover, knowledge of the device characteristics can be used to guide the simulated annealing process rather than introducing absolute randomness. The introduction of a degree of randomness adds flexibility during the iterative decoding that permits possible faster convergence times and convergence in situations where data may otherwise be uncorrectable.

Methods and apparatus are provided for soft data generation for memory devices based on a performance factor adjustment. At least one soft data value is generated for a memory device, by obtaining at least one read value; and generating the soft data value based on the obtained at least one read value and an adjustment based on one or more performance factors of the memory device. The read values may comprise, for example, data bits, voltage levels, current levels or resistance levels. The read values may be soft data or hard data. The possible performance factors include endurance, number of read cycles, retention time, temperature, process corner, inter-cell interference impact, location within the memory array and a pattern of aggressor cells. One or more pattern-dependent performance factors and / pr location-specific performance factors may also be considered. The generated soft data value may be a soft read value that is used to generate one or more log likelihood ratios, or may be the log likelihood ratios themselves.

A balance between customer satisfaction and cost to providing customer care can be achieved based on the use of online interaction classification techniques. Such techniques can use measurements such as a log likelihood ratio to determine if an interaction should be removed from automation.

Embodiments of the invention provide a method and device for determining channel reliability in polarization coding modulation. The method comprises: dividing a channel into m binary input channels, carrying out channel polarization transformation, and using a Gaussian approximation algorithm to calculate a log likelihood ratio Gaussian distribution mean corresponding to the polarization sub-channels according to the equivalent noise variance of the binary input channels obtained by splitting, so as to determine the reliability of the polarization sub-channels. Since the method provided by the invention adopts the Gaussian approximation algorithm, the problem of calculation complexity caused by calculating the channel reliability by using a density evolution tool is avoided. Compared with the scheme of calculating the channel reliability by using the density evolution tool, the calculation complexity of the method provided by the invention is obviously reduced.

A cooperative spatial multiplexing scheme in which the transmitter (source), equipped with a single antenna, forms virtual antenna arrays from a collection of distributed antennas belonging to different wireless terminals, and transmit a high-rate data stream to those terminals (relays). Each relay detects only a subset (called sub-stream) of the data stream and all relays forward their sub-streams simultaneously over the same physical channel. Then the receiver (destination) nulls and cancels the interference from different relays in order of the magnitude of log-likelihood ratio and detects the signal transmitted from the source.

A novel and useful apparatus for and method of multiple input multiple output (MIMO) detection for use in MIMO based communication systems. The mechanism of the invention performs a simplified tree search utilizing a single stage expansion of the most likely first symbol candidates, in the case of a 2×2 MIMO system. The invention also provides a refinement mechanism operative to significantly improve the soft information (i.e. log likelihood ratio) of the list of candidates. To improve the soft information, the mechanism applies one or more refinement rounds to generate additional candidates for both first and second detected symbols.

Data stored in non-volatile storage is decoded using iterative probabilistic decoding. An error correcting code such as a low density parity check code may be used. In one approach, initial reliability metrics, such as logarithmic likelihood ratios, are used in decoding sensed states of a set of non-volatile storage element. The decoding attempts to converge by adjusting the reliability metrics for bits in code words which represent the sensed state. Soft data bits are read from the memory if the decoding fails to converge. Initial reliability metric values are provided after receiving the hard read results and at each phase of the soft bit operation(s). In one embodiment, a second soft bit is read from the memory using multiple subsets of soft bit compare levels. While reading at the second subset of compare levels, decoding can be performed based on the first subset data.

A method for decoding Low Density Parity Check (LDPC) codes comprises executing a sum product algorithm to recover a set of information bits from an LDPC code represented as a bipartite graph of symbol nodes and check nodes, the sum product algorithm being responsive to input log likelihood ratios associated with the symbol nodes. The check nodes are updated by generating a set of forward difference metrics and a set of backward difference metrics in dependence on the ratios of logarithmic probabilities each associated with a corresponding symbol node of the LDPC code, updating each metric in the set of forward difference metrics in dependence on the absolute value of the log likelihood ratio associated with the symbol node and the absolute value of the previous metric in the set, updating each metric in the set of backward difference metrics in dependence on the absolute value of the log likelihood ratio associated with the symbol node and the absolute value of the previous metric in the set, and generating log likelihood ratios to be propagated back to each symbol node in dependence on the updated sets of forward and backward difference metrics.

A forward error correction method for decoding coded bits generated by low density parity check matrixes. The method comprises converting each of the coded bits into a log likelihood ratio (LLR) value, and applying the converted values to variable nodes; delivering messages applied to the variable nodes to check nodes; checking a message having a minimum value among the messages, and determining a sign of the message having the minimum value; receiving messages updated in the check nodes, adding up signs of the received messages and a sign of an initial message, applying a weighting factor of 1 when all signs are identical, and when all signs are not identical, updating a message of a variable node by applying a weighting factor; determining LLR of an initial input value; and hard-deciding values of the variable nodes, performing parity check on the hard decision values, and stopping the decoding when no error occurs.

Data stored in non-volatile storage is decoded using iterative probabilistic decoding. An error correcting code such as a low density parity check code may be used. In one approach, initial reliability metrics, such as logarithmic likelihood ratios, are used in decoding sensed states of a set of non-volatile storage elements. The decoding attempts to converge by adjusting the reliability metrics for bits in code words which represent the sensed state. Simulated annealing using an adjustable temperature parameter based on a level of error in the data read from the system can be performed to assist the iterative decoding process. The simulated annealing can introduce randomness, as noise for example, into the metric based decoding process. Moreover, knowledge of the device characteristics can be used to guide the simulated annealing process rather than introducing absolute randomness. The introduction of a degree of randomness adds flexibility during the iterative decoding that permits possible faster convergence times and convergence in situations where data may otherwise be uncorrectable.

A computational system can include digital circuitry and analog circuitry, for instance a digital processor and a quantum processor. The quantum processor can operate as a sample generator providing samples. Samples can be employed by the digital processing in implementing various machine learning techniques. For example, the computational system can perform unsupervised learning over an input space, for example via a discrete variational auto-encoder, and attempting to maximize the log-likelihood of an observed dataset. Maximizing the log-likelihood of the observed dataset can include generating a hierarchical approximating posterior. Unsupervised learning can include generating samples of a prior distribution using the quantum processor. Generating samples using the quantum processor can include forming chains of qubits and representing discrete variables by chains.