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.

An error correction encoding device includes an encoding unit to generate soft decision error correction frame information including a bit array of m rows and N columns obtained by combining first bit string group information and second bit string group information, the first bit string group information including a bit array of m rows and N1 columns in which it is enabled to perform pulse amplitude modulation of a combination of bit values of each column of the first bit string group information into a modulation symbol by using a first symbol mapping rule, the second bit string group information including a bit array of m rows and N2 columns in which it is enabled to perform pulse amplitude modulation of a combination of bit values of each column of the second bit string group information into a modulation symbol by using a second symbol mapping rule.

Disclosed is a 5.sup.th generation (5G) or a pre-5G communication system for supporting a data transmission rate higher than that of a 4.sup.th generation (4G) communication system such as long term evolution (LTE). An apparatus and a method for performing retransmission in a wireless communication system are provided. A method for operating a transmitting device in a wireless communication system, according to various embodiments of the present disclosure, comprises the steps of: transmitting a plurality of data code blocks (CBs) to at least one receiving device in an initial transmission step; receiving, from the at least one receiving device, feedback information including information for indicating the number of data CBs, from among the plurality of data CBs, for which decoding has failed; and transmitting the number of parity CBs, determined on the basis of the number of data CBs for which the decoding has failed, to the at least one receiving device in a retransmission step. Therefore, the resources required for retransmission can be reduced.

Techniques are described for wireless communication. One method includes segmenting a payload into a plurality of code blocks; generating, for each code block, a cyclic redundancy check (CRC); encoding each code block and associated CRC in one or more codewords of a plurality of codewords; and transmitting the codewords. The encoding is based at least in part on a low density parity check code (LDPCC) encoding type. Another method includes receiving a plurality of codewords associated with a payload encoded using a LDPCC encoding type; decoding a set of the codewords associated with the first payload and a CRC; and transmitting one of an acknowledgement (ACK) or a non-acknowledgement (NAK) for the set of the codewords.

A system and method for providing error control coding for backhaul applications are disclosed. Data is first encoded using Reed-Solomon (RS) coding. The output RS blocks are then turbo coded. The size of the output RS blocks is selected to match the input of the turbo encoder. The bits from the RS blocks may be interleaved to create the input turbo blocks. Cyclic Redundancy Check (CRC) parity bits may be added to the data prior to RS coding.

The present disclosure provides techniques for bandwidth constrained communication systems with frequency domain information processing. A bandwidth constrained equalized transport (BCET) communication system can include a transmitter, a communication channel, and a receiver. The transmitter can include a pulse-shaping filter that intentionally introduces memory into a signal in the form of inter-symbol interference, an error control code (ECC) encoder, a multidimensional fast Fourier transform (FFT) processing block that processes the signal in the frequency domain, and a first interleaver. The receiver can include an information-retrieving equalizer, a deinterleaver with an ECC decoder, and a second interleaver joined in an iterative ECC decoding loop. The communication system can be bandwidth constrained, and the signal can comprise an information rate that is higher than that of a communication system without intentional introduction of the memory at the transmitter.

Examples described herein include systems and methods which include wireless devices and systems with examples of mixing input data delayed versions of at least a portion of the respective processing results with coefficient data specific to a processing mode selection. For example, a computing system with processing units may mix the input data delayed versions of respective outputs of various layers of multiplication/accumulation processing units (MAC units) for a transmission in a radio frequency (RF) wireless domain with the coefficient data to generate output data that is representative of the transmission being processed according to a wireless processing mode selection. In another example, such mixing input data with delayed versions of processing results may be to receive and process noisy wireless input data. Examples of systems and methods described herein may facilitate the processing of data for 5G wireless communications in a power-efficient and time-efficient manner.

A power generation device includes a band gap reference (BGR) circuit configured to generate a reference voltage independent of an environmental change, and a voltage generation circuit configured to transfer an input power voltage based on a sum of the reference voltage and an internal ground voltage to generate an internal power voltage.

Example systems, read channels, and methods provide bit value detection from an encoded data signal using a neural network soft information detector. The neural network detector determines a set of probabilities for possible states of a data symbol from the encoded data signal. A soft output detector uses the set of probabilities for possible states of the data symbol to determine a set of bit probabilities that are iteratively exchanged as extrinsic information with an iterative decoder for making decoding decisions. The iterative decoder outputs decoded bit values for a data unit that includes the data symbol.

A method for decoding data by an electronic device (100) is provided. The method includes receiving, by the electronic device (100), encoded data. The method includes determining, by the electronic device (100), a sparsity of a plurality of Machine Learning (ML) models (301, 302) of a turbo decoder (150) of the electronic device (100) for decoding the encoded data based on Quality-of-Service (QoS) parameters. The method includes decoding, by the electronic device (100), the encoded data using the turbo decoder (150) based on the determined sparsity.