Methods, systems, and devices for wireless communication are described. The method, systems, and devices may include receiving a plurality of sets of input bits associated with respective transmission symbol periods at an encoder of a transmitting device, the plurality of sets of input bits associated with a single input vector to be encoded into a single codeword. The encoder may process the plurality of sets of input bits to generate a plurality of sets of output bits associated with respective transmission symbol periods, and output a first of the plurality of sets of output bits associated with a first of the plurality of sets of input bits prior receiving a second of the plurality of sets of input bits, the second of the plurality of sets of input bits being received at the encoder subsequent to the first of the plurality of sets of input bits.

The invention discloses a convolutional code decoder and a convolutional code decoding method. The convolutional code decoder and the convolutional code decoding method of the present invention perform decoding using predictive information, and therefore can demodulate/decode signals more quickly. Earlier completion of demodulation/decoding of signals can terminate the operation earlier and thereby achieve the effect of power savings. The convolutional code decoder performs decoding according to received data and auxiliary data to obtain target data, and includes a first error detection data generation circuit, a channel coding circuit, a first selection circuit, a first Viterbi decoding circuit, a second error detection data generation circuit, a comparison circuit, a second selection circuit, and a second Viterbi decoding circuit.

A decoding device includes a decode processing unit and a data temporary saving unit holding, of reception data to be input to the decode processing unit, a first number of pieces of reception data from a beginning of a frame and outputting the reception data being held after completion of inputting of one frame of the reception data to the decode processing unit. The decode processing unit includes a branch metric calculation unit, an ACS calculation unit calculating path metrics of the survivor paths based on the branch metric, a survivor path storage unit storing and holding a value determined based on each survivor path in each corresponding one of shift registers associated with the states, and an output selection unit outputting, among values output from the shift registers, a value associated with a path metric having the maximum likelihood among current path metrics, as a decoding result.

Certain aspects of the present disclosure relate to techniques and apparatus for increasing decoding performance and/or reducing decoding complexity. A transmitter may divide data of a codeword into two or more sections and then calculate redundancy check information (e.g., a cyclic redundancy check or a parity check) for each section and attach the redundancy check information to the codeword. A decoder of a receiver may decode each section of the codeword and check the decoding against the corresponding redundancy check information. If decoding of a section fails, the decoder may use information regarding section(s) that the decoder successfully decoded in re-attempting to decode the section(s) that failed decoding. In addition, the decoder may use a different technique to decode the section(s) that failed decoding. If the decoder is still unsuccessful in decoding the section(s), then the receiver may request retransmission of the failed section(s) or of the entire codeword.

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.

A convolutional decoder includes a first storage, a second storage, a branch metric processor to determine branch metrics for transitions of states from a start step to a last step according to input bit streams, an ACS processor to select maximum likelihood path metrics to determine a survival path according to the branch metrics and to update states of the start step to the first storage and the second storage alternately based on the selection of the maximum likelihood path metrics, and a trace back logic to selectively trace back the survival path based on the states of the start step stored in a selected storage among the first storage and the second storage.

Decoding of a first message is disclosed, wherein first and second messages are encoded by a code (represented by a state machine) to produce first and second code words, which are received over a communication channel. A plurality of differences (each corresponding to a hypothesized value of a part of the first message) between the first and second messages are hypothesized. An initial code word segment is selected having, as associated previous states, a plurality of initial states (each associated with a hypothesized difference and uniquely defined by the hypothesized value of the part of the first message). The first message is decoded by (for each code word segment, starting with the initial code word segment): determining first and second metrics associated with respective probabilities that the code word segment of the first and second code word (respectively) corresponds to a first message segment content, the probability of the second metric being conditional on the hypothesized difference of the initial state associated with the previous state of the state transition corresponding to the first message segment content, determining a decision metric by combining the first and second metrics, and selecting (for the first message) the first message segment content or a second message segment content based on the decision metric. If the first message segment content is selected, the subsequent state of the state transition corresponding to the first message segment content is associated with the initial state associated with the previous state of the state transition.

Decoding of a first message is disclosed, wherein first and second messages are encoded by a code (represented by a state machine) to produce first and second code words, which are received over a communication channel. A plurality of differences (each corresponding to a hypothesized value of a part of the first message) between the first and second messages are hypothesized. An initial code word segment is selected having, as associated previous states, a plurality of initial states (each associated with a hypothesized difference and uniquely defined by the hypothesized value of the part of the first message). The first message is decoded by (for each code word segment, starting with the initial code word segment): combining the code word segment of the first code word with a transformed (based on the hypothesized difference of the initial state associated with the previous state of the state transition corresponding to a first message segment content) code word segment of the second code word to produce a combined code word segment, determining a decision metric associated with a probability that the combined code word segment corresponds to the first message segment content, and selecting (for the first message) the first message segment content or a second message segment content based on the decision metric. If the first message segment content is selected, the subsequent state of the state transition corresponding to the first message segment content is associated with the initial state associated with the previous state of the state transition.

A method for processing a digital signal includes: receiving a plurality of protocol data units, each having a header including a plurality of control word bits; and a plurality of audio frames, each including a cyclic redundancy check code; decoding the protocol data units using an iterative decoding technique, wherein the iterative decoding technique uses a soft output decoding algorithm for iterations after the first iteration; and using decoded cyclic redundancy check codes to flag the audio frames containing errors. A receiver that implements the method is also provided.

A decoder having an input configured to receive a sequence of softbits presumed to correspond to a convolutionally-encoded codeword; and a decoding circuit configured to: determine, as part of a decoding process, a Maximum Likelihood (ML) survivor path in a trellis representation of the codeword; determine whether the presumed convolutionally-encoded codeword meets an early-termination criteria; and abort the decoding process if the presumed convolutionally-encoded codeword meets the early-termination criteria, continue the decoding process if the presumed convolutionally-encoded codeword fails to meet the early-termination criteria.