Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes polar encoding, with an encoder of the device, information bits and at least one parity bit using the polar code to obtain encoded data, and transmitting the encoded data to another device. The polar code comprises a plurality of sub-channels. The at least one parity bit being placed in at least one of the plurality of sub-channels. The at least one sub-channel is selected from the plurality of sub-channels based on a weight parameter.

Abstract: This application discloses a method: determining, based on a length of to-be-encoded information bits and a code rate, a code length N after encoding; determining, based on N, a minimum segment code length, and a maximum segment code length, a reserved segment quantity of each type of segments in segments of b?a+1 types of segment code lengths and a reserved code length corresponding to N, where the minimum segment code length is 2{circumflex over (?)}a, and the maximum segment code length is 2{circumflex over (?)}b; determining a segment quantity of each type of segments based on N, the reserved code length, a segment code length of each type of segments, and the reserved segment quantity of each type of segments, where N corresponds to S segments, and a segment code length of an ith segment in the S segments is greater than or equal to a segment code length of an (i+1)th segment in the S segments.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes allocating, from a set of sub-channels, one or more sub-channels for one or more parity bits based on row weights for sub-channels in a subset of sub-channels within the set of sub-channels, mapping information bits to remaining sub-channels in the set of sub-channels based on a reliability of the remaining sub-channels without mapping any of the information bits to the one or more sub-channels allocated for the one or more parity bits, polar encoding the information bits and the one or more parity bits based on at least the mapping of the information bits to the remaining sub-channels to obtain encoded bits, and transmitting the encoded bits to another device.

Abstract: Embodiments disclose an encoding method and a communications device. The method includes: obtaining and encoding a to-be-encoded information bit sequence based on a binary vector P1 of a first code, to obtain and output an encoded bit sequence, where P1 is determined based on a binary vector P2 of a second code and a binary vector P3 of a third code, P1, P2, and P3 indicate an information bit and a frozen bit of the first code, the second code and the third code respectively, a code length of the first code, the second code and the third code is n3, n2 and n3 respectively, a quantity of information bits of the first code, the second code and the third code is k1, k2 and k3 respectively, n1=n2*n3, and k1=k2*k3. Therefore, parallel decoding can be performed, helping reduce a decoding delay.

Abstract: A decoding method and apparatus are provided, to improve a degree of parallelism in decoded bit decisions and reduce a decoding delay. The method includes: performing a hard decision on each LLR in an inputted LLR vector having a length of M to obtain a first vector, where M?N and N is a length of to-be-decoded information; sequentially performing negation of some elements of the first vector to obtain L vectors; and then determining decoding results of the LLR vector based on the L vectors.

Abstract: A method comprises: obtaining a coded bit sequence by performing PC-polar coding on information bits based on first constructor parameters; and sending the coded bit sequence. A check equation of the first constructor parameters includes a first element representing a check-required information bit position and a second element representing a check bit position, the first element corresponds to a first vector (V1) in a generator matrix for PC-polar codes, the second element corresponds to a second vector (V2) in the generator matrix, and if a first Hamming weight (HW1) of V1 is the same as a second Hamming weight (HW2) of V2, then a third Hamming weight (HW3) of an addition modulo 2 vector is greater than HW1 and greater than HW2, or if HW1 is different from HW2, then HW3 is greater than a smaller one of the HW1 and HW2.

Abstract: A decoding method and apparatus are provided, to improve a degree of parallelism in decoded bit decisions and reduce a decoding delay. The method includes: performing a hard decision on each LLR in an inputted LLR vector having a length of M to obtain a first vector, where M?N and N is a length of to-be-decoded information; sequentially performing negation of some elements of the first vector to obtain L vectors; and then determining decoding results of the LLR vector based on the L vectors.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes polar encoding, with an encoder of the device, information bits and at least one parity bit using the polar code to obtain encoded data, and transmitting the encoded data to another device. The polar code comprises a plurality of sub-channels. The at least one parity bit being placed in at least one of the plurality of sub-channels. The at least one sub-channel is selected from the plurality of sub-channels based on a weight parameter.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes polar encoding, with an encoder of the device, information bits and at least one parity bit using the polar code to obtain encoded data, and transmitting the encoded data to another device. The polar code comprises a plurality of sub-channels. The at least one parity bit being placed in at least one of the plurality of sub-channels. The at least one sub-channel is selected from the plurality of sub-channels based on a weight parameter.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. The row weight for a sub-channel may be viewed as the number of “ones” in the corresponding row of the Kronecker matrix or as a power of 2 with the exponent (i.e. the hamming weight) being the number of “ones” in the binary representation of the sub-channel index (further described below). In one embodiment, candidate sub-channels that have certain row weight values are reserved for parity bit(s). Thereafter, K information bits may be mapped to the K most reliable remaining sub-channels, and a number of frozen bits (e.g. N?K) may be mapped to the least reliable remaining sub-channels. Parity bits may then mapped to the candidate sub-channels, and parity bit values are determined based on a function of the information bits.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. The row weight for a sub-channel may be viewed as the number of “ones” in the corresponding row of the Kronecker matrix or as a power of 2 with the exponent (i.e. the hamming weight) being the number of “ones” in the binary representation of the sub-channel index (further described below). In one embodiment, candidate sub-channels that have certain row weight values are reserved for parity bit(s). Thereafter, K information bits may be mapped to the K most reliable remaining sub-channels, and a number of frozen bits (e.g. N?K) may be mapped to the least reliable remaining sub-channels. Parity bits may then mapped to the candidate sub-channels, and parity bit values are determined based on a function of the information bits.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes allocating, from a set of sub-channels, one or more sub-channels for one or more parity bits based on row weights for sub-channels in a subset of sub-channels within the set of sub-channels, mapping information bits to remaining sub-channels in the set of sub-channels based on a reliability of the remaining sub-channels without mapping any of the information bits to the one or more sub-channels allocated for the one or more parity bits, polar encoding the information bits and the one or more parity bits based on at least the mapping of the information bits to the remaining sub-channels to obtain encoded bits, and transmitting the encoded bits to another device.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes allocating, from a set of sub-channels, one or more sub-channels for one or more parity bits based on row weights for sub-channels in a subset of sub-channels within the set of sub-channels, mapping information bits to remaining sub-channels in the set of sub-channels based on a reliability of the remaining sub-channels without mapping any of the information bits to the one or more sub-channels allocated for the one or more parity bits, polar encoding the information bits and the one or more parity bits based on at least the mapping of the information bits to the remaining sub-channels to obtain encoded bits, and transmitting the encoded bits to another device.

Abstract: A method comprises: obtaining a coded bit sequence by performing PC-polar coding on information bits based on first constructor parameters; and sending the coded bit sequence. A check equation of the first constructor parameters includes a first element representing a check-required information bit position and a second element representing a check bit position, the first element corresponds to a first vector (V1) in a generator matrix for PC-polar codes, the second element corresponds to a second vector (V2) in the generator matrix, and if a first Hamming weight (HW1) of V1 is the same as a second Hamming weight (HW2) of V2, then a third Hamming weight (HW3) of an addition modulo 2 vector is greater than HW1 and greater than HW2, or if HW1 is different from HW2, then HW3 is greater than a smaller one of the HW1 and HW2.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes allocating, from a set of sub-channels, one or more sub-channels for one or more parity bits based on row weights for sub-channels in a subset of sub-channels within the set of sub-channels, mapping information bits to remaining sub-channels in the set of sub-channels based on a reliability of the remaining sub-channels without mapping any of the information bits to the one or more sub-channels allocated for the one or more parity bits, polar encoding the information bits and the one or more parity bits based on at least the mapping of the information bits to the remaining sub-channels to obtain encoded bits, and transmitting the encoded bits to another device.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. In one example, an embodiment technique includes polar encoding, with an encoder of the device, information bits and at least one parity bit using the polar code to obtain encoded data, and transmitting the encoded data to another device. The polar code comprises a plurality of sub-channels. The at least one parity bit being placed in at least one of the plurality of sub-channels. The at least one sub-channel is selected from the plurality of sub-channels based on a weight parameter.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. The row weight for a sub-channel may be viewed as the number of “ones” in the corresponding row of the Kronecker matrix or as a power of 2 with the exponent (i.e. the hamming weight) being the number of “ones” in the binary representation of the sub-channel index (further described below). In one embodiment, candidate sub-channels that have certain row weight values are reserved for parity bit(s). Thereafter, K information bits may be mapped to the K most reliable remaining sub-channels, and a number of frozen bits (e.g. N?K) may be mapped to the least reliable remaining sub-channels. Parity bits may then mapped to the candidate sub-channels, and parity bit values are determined based on a function of the information bits.

Abstract: Embodiment techniques map parity bits to sub-channels based on their row weights. The row weight for a sub-channel may be viewed as the number of “ones” in the corresponding row of the Kronecker matrix or as a power of 2 with the exponent (i.e. the hamming weight) being the number of “ones” in the binary representation of the sub-channel index (further described below). In one embodiment, candidate sub-channels that have certain row weight values are reserved for parity bit(s). Thereafter, K information bits may be mapped to the K most reliable remaining sub-channels, and a number of frozen bits (e.g. N?K) may be mapped to the least reliable remaining sub-channels. Parity bits may then mapped to the candidate sub-channels, and parity bit values are determined based on a function of the information bits.