Abstract: An embodiment of a method for channel estimation for an Orthogonal Frequency Division Multiplexing communication system, including estimating a Time Domain Least Squares channel impulse response having a given maximum number of L taps based on a channel covariance matrix Q, and for each tap l=1, . . . , L a respective channel impulse response in the time-domain ?l, wherein the channel impulse responses in the time-domain are grouped as a channel impulse response vector in the time domain ?. Specifically, an updated channel-impulse-response vector in the time domain {tilde over (h)} is determined by computing for each tap l the solution of the following system: Q1:l, 1:l{tilde over (h)}l×1=?1:l, wherein the updated channel-impulse-response vector in the time domain {tilde over (h)} is computed recursively via a Levinson Durbin algorithm.

Abstract: An embodiment of an arrangement detects sequences of digitally modulated symbols from multiple sources. The arrangement identifies a suitable set of candidate values for at least one transmitted sequence of symbols and determines for each candidate value a set of sequences of transmitted symbols. The arrangement estimates at least one further set of sequences of transmitted symbols, calculates a metric for each sequence of transmitted symbols, and selects the sequence that maximizes the metric. At the end, a-posteriori bit soft output information for the selected sequence is calculated from the metrics for said sequences. Generally, these calculations are based on the information coming from a channel-state-information matrix and a-priori information on the modulated symbols from a second module, such as a forward error-correction-code (ECC) decoder.

Abstract: Subject matter, for example, disclosed herein relates to an embodiment of a process, system, device, or article involving error correction codes. In a particular embodiment, an error-correcting device may comprise an input port to receive an error correcting code (ECC) based, at least in part, on contents of a memory array; a nonlinear computing block to process the ECC to provide a plurality of signals representing a nonlinear portion of an error locator polynomial; and a linear computing block to process the ECC concurrently with processing the ECC to provide a plurality of signals representing the nonlinear portion of the error locator polynomial, to provide a plurality of signals representing a linear portion of the error locator polynomial.

Abstract: Subject matter disclosed herein relates to memory operations regarding error correction or error detection.

Abstract: An embodiment of a method and device for detecting a signal and generating bit soft-output of a multiple-input multiple-output system is provided. The device includes at least one channel estimates pre-processing unit, one received vector processing and one detection and soft-output generation unit. The pre-processing unit calculates multiple QR Decompositions of the input channel estimation matrix. The detection and soft-output generation unit computes near optimal bit soft output information with a deterministic complexity and latency. It may implement a reduced complexity search method. Globally, embodiments of the invention may allow achieving low complexity, high data rate, scalability in terms of the dimension of the MIMO system and flexibility versus the supported modulation order, all potentially key factors for most MIMO wireless transmission applications.

Abstract: An embodiment of an arrangement detects sequences of digitally modulated symbols from multiple sources. The arrangement identifies a suitable set of candidate values for at least one transmitted sequence of symbols and determines for each candidate value a set of sequences of transmitted symbols. The arrangement estimates at least one further set of sequences of transmitted symbols, calculates a metric for each sequence of transmitted symbols, and selects the sequence that maximizes the metric. At the end, a-posteriori bit soft output information for the selected sequence is calculated from the metrics for said sequences. Generally, these calculations are based on the information coming from a channel-state-information matrix and a-priori information on the modulated symbols from a second module, such as a forward error-correction-code (ECC) decoder.

Abstract: An embodiment of a method for channel estimation for an Orthogonal Frequency Division Multiplexing communication system, including estimating a Time Domain Least Squares channel impulse response having a given maximum number of L taps based on a channel covariance matrix Q, and for each tap l=1, . . . , L a respective channel impulse response in the time-domain ?l, wherein the channel impulse responses in the time-domain are grouped as a channel impulse response vector in the time domain ?. Specifically, an updated channel-impulse-response vector in the time domain {tilde over (h)} is determined by computing for each tap l the solution of the following system: Q1:l, 1:l{tilde over (h)}l×1=?1:l, wherein the updated channel-impulse-response vector in the time domain {tilde over (h)} is computed recursively via a Levinson Durbin algorithm.

Abstract: Subject matter, for example, disclosed herein relates to an embodiment of a process, system, device, or article involving error correction codes. In a particular embodiment, an error-correcting device may comprise an input port to receive an error correcting code (ECC) based, at least in part, on contents of a memory array; a nonlinear computing block to process the ECC to provide a plurality of signals representing a nonlinear portion of an error locator polynomial; and a linear computing block to process the ECC concurrently with processing the ECC to provide a plurality of signals representing the nonlinear portion of the error locator polynomial, to provide a plurality of signals representing a linear portion of the error locator polynomial.

Abstract: A method of channel estimation in orthogonal frequency-division multiplexing communication employing three or more subcarriers, wherein frequency correlation exists between the subcarriers. The method includes: calculating a coarse channel estimate for each of the subcarriers, and calculating from the coarse channel estimates refined channel estimates for each of the subcarriers, wherein calculation of the refined channel estimates includes calculating the parameters of a Wiener Filter having a length of 2 L+1, where L is a positive integer, and filtering the coarse channel estimates with the Wiener Filter.

Abstract: An embodiment of an arrangement for detecting sequences of digitally modulated symbols from multiple sources. The arrangement identifies a suitable set of candidate values for at least one transmitted sequence of symbols and determines for each candidate value a set of sequences of transmitted symbols. The arrangement estimates at least one further set of sequence of transmitted symbols, calculates a metric for each sequence of transmitted symbols and selects the sequence that maximizes the metric. At the end, a-posteriori bit soft output information for the selected sequence is calculated from the metrics for said sequences. Generally, these calculations are base on the information coming from a channel state information matrix and a-priori information on said modulated symbols from a second module, such as a forward error correction code decoder.

Abstract: An embodiment of a method and device for detecting a signal and generating bit soft-output of a multiple-input multiple-output system is provided. The device includes at least one channel estimates pre-processing unit, one received vector processing and one detection and soft-output generation unit. The pre-processing unit calculates multiple QR Decompositions of the input channel estimation matrix. The detection and soft-output generation unit computes near optimal bit soft output information with a deterministic complexity and latency. It may implement a reduced complexity search method. Globally, embodiments of the invention may allow achieving low complexity, high data rate, scalability in terms of the dimension of the MIMO system and flexibility versus the supported modulation order, all potentially key factors for most MIMO wireless transmission applications.

Abstract: A method of channel estimation in orthogonal frequency-division multiplexing communication employing three or more subcarriers, wherein frequency correlation exists between the subcarriers. The method includes: calculating a coarse channel estimate for each of the subcarriers, and calculating from the coarse channel estimates refined channel estimates for each of the subcarriers, wherein calculation of the refined channel estimates includes calculating the parameters of a Wiener Filter having a length of 2 L+1, where L is a positive integer, and filtering the coarse channel estimates with the Wiener Filter.

Abstract: An embodiment of an arrangement for detecting sequences of digitally modulated symbols from multiple sources. The arrangement identifies a suitable set of candidate values for at least one transmitted sequence of symbols and determines for each candidate value a set of sequences of transmitted symbols. The arrangement estimates at least one further set of sequence of transmitted symbols, calculates a metric for each sequence of transmitted symbols and selects the sequence that maximizes the metric. At the end, a-posteriori bit soft output information for the selected sequence is calculated from the metrics for said sequences. Generally, these calculations are base on the information coming from a channel state information matrix and a-priori information on said modulated symbols from a second module, such as a forward error correction code decoder.

Abstract: Maximum Likelihood Sequence Estimation (MLSE) is performed on a received signal that is affected by non-linear distortion. In particular, a cleaned signal is produced by removing non-linear inter-symbol-interference (ISI) through a Volterra canceller which is a simplified structure with respect to a Volterra Equalizer. The latter only processes the non-linear distortion. Finally, a Viterbi Detector is used to process the cleaned signal in the manner of a linear signal, and to estimate appropriate metrics accordingly.