A low density parity check (LDPC) channel encoding method is used in a wireless communications system. A communication device encodes an input bit sequence by using an LDPC matrix, to obtain an encoded bit sequence for transmission. The LDPC matrix is obtained based on a lifting factor Z and a base matrix. The base matrix may be one of eight exemplary designs. The encoding method can be used in various communications systems including fifth generation (5G) telecommunication systems, and can support various encoding requirements for information bit sequences with different code lengths.

Apparatus and methods are disclosed for transmitting and receiving data in a wireless communication network. Apparatus for transmitting data in a wireless communication network comprises a real modulation branch for modulating a first segment of a bit sequence to obtain a real modulated signal, a complex modulation branch for modulating a second segment of the bit sequence to obtain a complex modulated signal, a signal dividing unit configured to divide the bit sequence into a plurality of alternating first segments and second segments, and to send the first segments and the second segments to the real modulation branch and the complex modulation branch respectively, and a transmitter configured to transmit the real and complex modulated signals. Apparatus and methods are also disclosed for demultiplexing a plurality of data streams, using wide linear zero forcing with successive interference cancellation.

A method implemented in a computer system includes training a network, which is obtained by unfolding an iterative algorithm for demodulation or demodulation and decoding, using a machine learning technique with a loss function that takes into account non-Gaussianity of a log-likelihood ratio (LLR) distribution calculated from an output of the network. The method further includes producing a first set of learned parameters of that iterative algorithm.

A method includes calculating a number of iterative detection and decoding (IDD) iterations and a number of decoding iterations for each of a plurality of channel coding units in a target codeword; calculating a demodulation time and a decoding time for the target codeword based on the number of IDD iterations and the number of decoding iterations for the target codeword; adding the target codeword to a codeword set, based on a demodulation time and a decoding time for codewords in the codeword set and the target codeword; and performing an IDD operation based on a number of IDD iterations and a number of decoding iterations.

There is provided a decoding circuit including; a first decoding unit that decodes a first signal from a multiplexed signal in which the first signal and a second signal are multiplexed in an LDM (Layered Division Multiplexing) system; and a second decoding unit that decodes the second signal from the multiplexed signal using the decoding result of the decoded first signal, wherein the second signal is selectively decoded based on noise information related to a reception state of the multiplexed signal.

An operation method of a receiving apparatus may comprise: receiving an N-th data block belonging to a frame including a plurality of data blocks from a transmitting apparatus, each of the plurality of data blocks including a data period and a UW period; storing a first UW received in a UW period of the N-th data block in a buffer; receiving an (N+1)-th data block belonging to the frame from the transmitting apparatus; estimating a phase noise in a time domain by combining the first UW with a second UW received in a UW period of the (N+1)-th data block; and applying time-domain compensation according to the estimated phase noise to the (N+1)-th data block, and demodulating data of the (N+1)-th data block, wherein the first UW and the second UW are configured with a same sequence.

Methods and apparatus for decoding received uplink transmissions using log-likelihood ratio optimization. In an embodiment, a method includes soft-demapping resource elements based on soft-demapping parameters as part of a process to generate log-likelihood ratios (LLR) values, decoding the LLRs to generate decoded data, and identifying a target performance value. The method also includes determining a performance metric from the decoded data, and performing a machine learning algorithm that dynamically adjusts the soft-demapping parameters to move the performance metric toward the target performance value.

A method for mitigating interference in a frequency hopping channel system based on codeword metrics obtained during decoding of codewords. The method includes decoding a plurality of codewords using a particular error control coding method. Each of the plurality of codewords includes portions received from plurality of channels in the frequency hopping channel system. For each decoded codeword, one or more codeword metrics are obtained based on the cost of correcting errors during decoding of the plurality of codewords. Based on the codeword metrics, one or more channel metrics are inferred. Based on the inferred one or more channel metrics, a reliability metric of a particular channel is reduced, or incoming symbols received from the particular channel are ignored during decoding.

A method for generating a code, a method for encoding and decoding data, and an encoder and a decoder performing the encoding and decoding are disclosed. In an embodiment, a method for lifting a child code from a base code for encoding and decoding data includes determining a single combination of a circulant size, a lifting function, and a labelled base matrix PCM according to an information length and a code rate using data stored in a lifting table. The lifting table was defined at a code generation stage. The method also includes calculating a plurality of shifts for the child code. Each shift is calculated by applying the lifting function to the labelled base matrix PCM with a defined index using the circulant size and using the derived child PCM to encode or decode data.

Disclosed is a precoding method for generating, from a plurality of baseband signals, a plurality of precoded signals that are transmitted in the same frequency bandwidth at the same time. According to the precoding method, one matrix is selected from among matrices defining a precoding process that is performed on the plurality of baseband signals by hopping between the matrices. A first baseband signal and a second baseband signal relating to a first coded block and a second coded block generated by using a predetermined error correction block coding scheme satisfy a given condition.