An apparatus includes a memory and a controller. The memory may be configured to store data. The memory generally comprises a plurality of memory units each having a size less than a total size of the memory. The controller may be configured to generate a set of converted log likelihood ratios by scaling a set of original log likelihood ratios using a selected scalar value, wherein the controller determines the selected scalar value by generating a plurality of sets of scaled log likelihood ratios by scaling the set of original log likelihood ratios with a plurality of corresponding scalar values, calculating a plurality of respective correlation coefficients each measuring a similarity of a respective set of scaled log likelihood ratios to the set of original log likelihood ratios, and selecting the scalar value corresponding to the set of scaled log likelihood ratios whose respective correlation coefficient is highest as the selected scalar value.

Embodiments described herein provide a system for dynamically selecting a pre-processing scheme for an LDPC decoder. The system includes a receiver configured to detect transmission of a first data packet and receive a first set of data bits corresponding to a first portion of the first data packet. The system further includes a histogram generator configured to calculate log-likelihood ratios for each data bit from the first set of data bits, and generate a histogram based on the calculated log-likelihood ratios. The receiver is configured to continue receiving a second set of data bits corresponding to a second portion of the first data packet. The system further includes a selector configured to activate or inactivate a log-likelihood ratio pre-processing scheme on the received second set of data bits based on characteristics of the histogram.

A mobile device includes a display, a mobile-communication modem including a Viterbi decoder (VD) configured to decode a tail biting convolutional code (TBCC)-encoded data, a memory coupled to the mobile-communication modem, and a wireless antenna coupled to the mobile-communication modem and to receive a Physical Downlink Control Channel (PDCCH). The VD is configured to: receive data encoded by TBCC; select a candidate to initiate a training section; determine final path metric (PM) values of possible states at a last step of the training section; determine a PM-related value based on the final PM values of the possible states; and determine an early termination of a decoding for the candidate based on the PM-related value.

Techniques are described for an adaptive low density parity check (LDPC) decoder. The techniques include receiving a first set of values corresponding to a first low density parity check codeword and noise, performing a first plurality of iterations of an iterative decoding algorithm using a first set of decoding parameters to decode the received first set of values, comparing a metric with a first threshold, and upon determining that the metric is larger than the threshold: selecting a second set of decoding parameters for the iterative LDPC decoder and performing a second plurality of iterations of the iterative LDPC decoding algorithm using the second set of decoding parameters to decode the received first set of values and generate a first set of decoded bits.

A three-dimensional data encoding method includes: generating an N-ary tree structure of three-dimensional points included in three-dimensional data, where N is an integer greater than or equal to 2; generating first encoded data by encoding a first branch using a first encoding process, the first branch having, as a root, a first node included in a first layer that is one of layers included in the N-ary tree structure; generating second encoded data by encoding a second branch using a second encoding process different from the first encoding process, the second branch having, as a root, a second node included in the first layer and different from the first node; and generating a bitstream including the first encoded data and the second encoded data.

Systems and methods for decoding block and concatenated codes are provided, including channel state information estimation such as by using optimum filter lengths based on channel selectivity and adaptive decision-directed channel estimation. These improvements enhance the performance of various communication systems and consumer electronics, including HD Radio receivers and systems.

A system implements adaptive desaturation for the min-sum decoding of LDPC codes. Specifically, when an-above threshold proportion of messages from check nodes to variable nodes (CN-to-VN messages) are saturated to a maximum fixed-precision value, all CN-to-VN messages are halved. This facilitates the saturation of correct messages and boosts error correction over small trapping sets. The adaptive desaturation approach reduces the error floor by orders of magnitudes with negligible add-on circuits.

A decoder includes syndrome storage and a first barrel shifter configured to bit-shift hard decision bit data to generate shifted data that is aligned with a set of syndromes from the syndrome storage. The decoder also includes a first syndrome update circuit coupled to the first barrel shifter and configured to process the set of syndromes based on the shifted data to generate an updated version of the set of syndromes. The decoder may also be configured to perform on-the-fly syndrome weight computation.

A system implements adaptive desaturation for the min-sum decoding of LDPC codes. Specifically, when an-above threshold proportion of messages from check nodes to variable nodes (CN-to-VN messages) are saturated to a maximum fixed-precision value, all CN-to-VN messages are halved. This facilitates the saturation of correct messages and boosts error correction over small trapping sets. The adaptive desaturation approach reduces the error floor by orders of magnitudes with negligible add-on circuits.

A soft output detector is programmed with a first set of parameters. Soft information is generated according to the first set of parameters, including likelihood information that spans a maximum likelihood range. Error correction decoding is performed on the soft information generated according to the first set of parameters. In the event decoding is unsuccessful, the soft output detector is programmed with a second set of parameters, soft information according is generated to the second set of parameters (including likelihood information that is scaled down from the maximum likelihood range), and error correction decoding is performed on the soft information generated according to the second set of parameters.