US-12621010-B2 - On-demand decoding method and apparatus

US12621010B2US 12621010 B2US12621010 B2US 12621010B2US-12621010-B2

Abstract

This application discloses decoding methods, apparatuses, and computer-readable storage media, which may be applied to a plurality of scenarios such as a metropolitan area network, a backbone network, and data center interconnection. An example method includes: obtaining syndromes corresponding to a plurality of codewords; grouping the syndromes into groups; and sorting priorities of each group of syndromes; and selecting, based on a priority sorting result of each group of syndromes, a syndrome for decoding.

Inventors

Wai Kong Raymond Leung
Kechao HUANG
Huixiao Ma
Shiyao XIAO
Dongyu Geng

Assignees

HUAWEI TECHNOLOGIES CO., LTD.

Dates

Publication Date: 20260505
Application Date: 20221227
Priority Date: 20200703

Claims (20)

1 . A decoding method, comprising: receiving a plurality of codewords transmitted by an encoding apparatus through a communication channel; obtaining a plurality of syndromes, each of the plurality of syndromes corresponding to one of the plurality of codewords, wherein the plurality of syndromes are in a plurality of groups of syndromes, the plurality of groups of syndromes are n groups of syndromes, n is a positive integer not greater than a quantity of decoding processes performed in parallel, and each of the plurality of syndromes has a corresponding priority; and for each group of the plurality of groups of syndromes, identifying a syndrome from syndromes in the group for decoding based on priorities of the syndromes in the group, wherein identifying the syndrome for each group of the plurality of groups of syndromes comprises: identifying a first syndrome from a plurality of first syndromes in a first group of the plurality of groups based on a plurality of first priorities of the plurality of first syndromes in the first group; and identifying a second syndrome from a plurality of second syndromes in a second group of the plurality of groups based on a plurality of second priorities of the plurality of second syndromes in the second group.
2 . The decoding method according to claim 1 , wherein a priority of a non-zero syndrome is higher than a priority of a syndrome whose value is 0.
3 . The decoding method according to claim 1 , wherein a priority of a non-zero syndrome decoded a large quantity of times is lower than a priority of a non-zero syndrome decoded a small quantity of times.
4 . The decoding method according to claim 1 , wherein the decoding method is applied to a decoding apparatus that comprises a plurality of decoding units; and wherein the method comprises: obtaining selected syndromes by selecting a maximum of one syndrome from each group of the plurality of groups of syndromes; and separately sending the selected syndromes to different decoding units for hard decision or soft decision decoding, wherein all the selected syndromes are non-zero syndromes.
5 . The decoding method according to claim 1 , wherein the decoding method is applied to a decoding apparatus that comprises a plurality of decoding units; and wherein the method comprises: obtaining selected syndromes by selecting one syndrome from each group of the plurality of groups of syndromes; and separately sending the selected syndromes to different decoding units for soft decision decoding.
6 . The decoding method according to claim 4 , wherein a quantity of groups of the plurality of groups of syndromes is the same as a quantity of decoding units.
7 . The decoding method according to claim 1 , wherein the decoding method is applied to a decoding apparatus that comprises a plurality of decoding units; and wherein the method comprises: obtaining first selected syndromes by selecting a maximum of one syndrome from each group of the plurality of groups of syndromes; separately sending the first selected syndromes to different decoding units for hard decision or soft decision decoding; sorting priorities of every two groups of syndromes; obtaining second selected syndromes by selecting a maximum of one syndrome from every two groups based on a sorting result; and separately sending the second selected syndromes to different decoding units for hard decision or soft decision decoding, wherein the first selected syndromes and the second selected syndromes are different, and all the first selected syndromes and the second selected syndromes are non-zero syndromes.
8 . The decoding method according to claim 1 , wherein the decoding method is applied to a decoding apparatus that comprises a plurality of decoding units; and wherein the method comprises: obtaining first selected syndromes by selecting one syndrome from each group of the plurality of groups of syndromes; separately sending the first selected syndromes to different decoding units for soft decision decoding; sorting priorities of every two groups of syndromes; obtaining second selected syndromes by selecting one syndrome from every two groups based on a sorting result; and separately sending the second selected syndromes to different decoding units for soft decision decoding, wherein the first selected syndromes and the second selected syndromes are different.
9 . The decoding method according to claim 7 , wherein the plurality of groups of syndromes are 2/3n groups, n is a quantity of decoding units, and n is an integer multiple of 3.
10 . The decoding method according to claim 1 , wherein all groups comprise a same quantity of syndromes.
11 . The decoding method according to claim 1 , wherein after decoding the identified syndromes, the method further comprises: sorting priorities of each group of the plurality of groups of syndromes again; and selecting, based on a current priority sorting result, a maximum of one syndrome from each group of the plurality of groups of syndromes for decoding.
12 . The decoding method according to claim 11 , wherein in the two sorting the priorities of each group of the plurality of groups of syndromes, priority sorting methods are different.
13 . The decoding method according to claim 1 , wherein the method further comprises: if a first syndrome is successfully decoded, obtaining a delta syndrome corresponding to the first syndrome and a flip bit, wherein the first syndrome is one of syndromes for decoding; superimposing the delta syndrome and the first syndrome to obtain an updated syndrome; and flipping, based on the flip bit, a bit that is in a corresponding codeword and that corresponds to the flip bit.
14 . The decoding method according to claim 1 , wherein all syndromes have same storage time.
15 . The decoding method according to claim 1 , wherein the method further comprises: storing, in groups, syndromes corresponding to a first frame, wherein quantities of syndromes that correspond to the first frame and that are stored in the groups differ by a maximum of one, and the first frame comprises a plurality of codewords.
16 . A decoding apparatus, comprising a receiver, a controller, and a decoder, wherein: the receiver is configured to receive a plurality of codewords transmitted by an encoding apparatus through a communication channel; and the controller is configured to: obtain a plurality of syndromes, each of the plurality of syndromes corresponding to one of the plurality of codewords, wherein the plurality of syndromes are in a plurality of groups of syndromes, the plurality of groups of syndromes are n groups of syndromes, n is a positive integer not greater than a quantity of decoding processes performed in parallel, and each of the plurality of syndromes has a corresponding priority; for each group of the plurality of groups of syndromes, identify a syndrome from syndromes in the group for decoding based on priorities of the syndromes in the group, wherein identifying the syndrome for each group of the plurality of groups of syndromes comprises: identifying a first syndrome from a plurality of first syndromes in a first group of the plurality of groups based on a plurality of first priorities of the plurality of first syndromes in the first group; and identifying a second syndrome from a plurality of second syndromes in a second group of the plurality of groups based on a plurality of second priorities of the plurality of second syndromes in the second group; and send the identified syndromes to the decoder.
17 . The decoding apparatus according to claim 16 , wherein a priority of a non-zero syndrome is higher than a priority of a syndrome whose value is 0.
18 . The decoding apparatus according to claim 16 , wherein a priority of a non-zero syndrome decoded a large quantity of times is lower than a priority of a non-zero syndrome decoded a small quantity of times.
19 . A non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores instructions which, when executed by one or more processors of a terminal device, cause the terminal device to perform operations comprising: receiving a plurality of codewords transmitted by an encoding apparatus through a communication channel; obtaining a plurality of syndromes, each of the plurality of syndrome corresponding to one of the plurality of codewords, wherein the plurality of syndromes are in a plurality of groups of syndromes, the plurality of groups of syndromes are n groups of syndromes, n is a positive integer not greater than a quantity of decoding processes performed in parallel, and each of the plurality of syndromes has a corresponding priority; and for each group of the plurality of groups of syndromes, identifying a syndrome from syndromes in the group for decoding based on priorities of the syndromes in the group, wherein identifying the syndrome for each group of the plurality of groups of syndromes comprises: identifying a first syndrome from a plurality of first syndromes in a first group of the plurality of groups based on a plurality of first priorities of the plurality of first syndromes in the first group; and identifying a second syndrome from a plurality of second syndromes in a second group of the plurality of groups based on a plurality of second priorities of the plurality of second syndromes in the second group.
20 . The non-transitory computer-readable storage medium according to claim 19 , wherein a priority of a non-zero syndrome is higher than a priority of a syndrome whose value is 0.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation of International Application No. PCT/CN2021/104390, filed on Jul. 3, 2021, which claims priority to Chinese Patent Application No. 202010631750.4, filed on Jul. 3, 2020. The disclosures of the aforementioned applications are hereby incorporated by reference in their entireties. TECHNICAL FIELD This application relates to a decoding technology, and in particular, to a low-power-consumption on-demand decoding technology. BACKGROUND A forward error correction (Forward Error Correction, FEC) encoding technology is widely used in wireless cellular, wireless network, storage, and high-speed optical transmission systems. A start point of the forward error correction encoding technology is to add some check bits when a transmitter performs encoding and to calculate the check bits in a receive end bitstream in which a bit error occurs to correct the bit error in the bitstream, to reduce a signal-to-noise ratio (Optical Signal Noise Ratio, OSNR) tolerance of a receive end, thereby improving bit error rate performance of the system, improve reliability of system communication, prolong a signal transmission distance, reduce transmit power of the transmitter, and reduce system costs. In recent years, the optical communications system has been rapidly developed from 100 Gbps to 400 Gbps, and further developed to a future optical communications system of 800 Gbps, imposing a higher requirement on an FEC encoding gain and also causing FEC encoding to be closer to a Shannon limit. Consequently, FEC decoding is becoming more complex, and decoding power consumption is becoming higher, and therefore a product requirement cannot be met. SUMMARY This application provides a decoding method, to sort priorities of input codewords and perform on-demand decoding scheduling, to resolve a problem that decoding complexity is high and decoding power consumption is high in the conventional technology. According to a first aspect, a decoding method is provided. The method includes: obtaining a syndrome corresponding to each of a plurality of codewords; grouping obtained syndromes, and sorting priorities of each group of syndromes; and selecting, based on a priority sorting result of each group of syndromes, a syndrome for decoding. In this embodiment of this application, same decoding processing is not performed on syndromes of all codewords, to avoid a problem that a same quantity of decoding times need to be performed regardless of whether codewords are correct in a conventional static decoding solution, thereby implementing on-demand decoding and reducing a decoding resource requirement and system power consumption. In a possible implementation, a priority of a non-zero syndrome is higher than a priority of a syndrome whose value is 0. Further, a priority of a non-zero syndrome decoded a large quantity of times is lower than a priority of a non-zero syndrome decoded a small quantity of times. In addition, a quantity of decoding times may be further limited. When a quantity of times of decoding a syndrome reaches a threshold, the syndrome is no longer decoded. For example, the threshold may be set to three times, and provided that the quantity of times of decoding the syndrome reaches 3, the syndrome is no longer decoded. More opportunities are provided for decoding a syndrome that needs to be decoded, thereby improving decoding efficiency. Optionally, in a case of hard decision, a priority of a non-zero syndrome is always higher than a priority of a syndrome whose value is 0. In a case of soft decision decoding, a priority of a non-zero syndrome may always be higher than a priority of a syndrome whose value is 0, or a quantity of decoding times may be preferential. For example, regardless of whether a value of a syndrome is 0, a priority of a syndrome decoded a large quantity of times is lower than a priority of a syndrome decoded a small quantity of times, and if two syndromes are decoded a same quantity of times, a priority of a non-zero syndrome is higher than a priority of a syndrome whose value is 0. In addition, when soft decision decoding is used, priority sorting may be alternatively performed based on reliability of soft information. This is not limited in this application. In a possible implementation, the decoding method is applied to a decoding apparatus that includes a plurality of decoding units. The selecting a syndrome for decoding includes: selecting a maximum of one syndrome from each group, and separately sending selected syndromes to different decoding units for hard decision or soft decision decoding, where all the selected syndromes are non-zero syndromes. Because when hard decision decoding is used, a syndrome whose value is 0 does not need to be decoded, if values of all syndromes in a group are 0, no syndrome in the group is selected for decoding, and therefore a maximum of one syndrome is selected from each group. In this case, a storage