Transmission quality is improved in an environment in which direct waves dominate in a transmission method for transmitting a plurality of modulated signals from a plurality of antennas at the same time. All data symbols used in data transmission of a modulated signal are precoded by hopping between precoding matrices so that the precoding matrix used to precode each data symbol and the precoding matrices used to precode data symbols that are adjacent to the data symbol in the frequency domain and the time domain all differ. A modulated signal with such data symbols arranged therein is transmitted.

The present invention relates to a method and an apparatus for transmitting interference related control information in order to improve reception performance of a UE which receives a downlink signal, in a cellular mobile communication system based on an Long Term Evolution-Advanced (LTE-A) system. A communication method includes receiving, from a base station, resource allocation information on resource allocation granularity for a neighbor cell associated with an interference signal; identifying the resource allocation granularity for the neighbor cell; and performing an interference cancellation for the interference signal based on the resource allocation granularity for the neighbor cell.

A machine-learning based multiple-input, multiple-output (MIMO) demapper for a wireless device may include a classifier that selects which MIMO demapper to use for a sample for a particular tone. For example, a wireless device may receive via a plurality of antennas a plurality of signals including a plurality of tones. The wireless device may determine selection features for each tone of the plurality of tones. The wireless device may select, for each tone, by the classifier based on the selection features, a selected demapper from at least a first MIMO demapper and a second MIMO demapper. The second MIMO demapper may have a different performance characteristic than the first MIMO demapper. The wireless device may detect, for each tone, one or more streams using the selected demapper for the tone. A stream may refer to a sequence of bits.

A communication device determines that a data rate of a data packet exceeds a threshold, and in response, lowers a processing speed of an equalizer device to prevent a buffer from overflowing. The buffer stores outputs generated by the equalizer device. A forward error correction code decoder device of the communication device processes outputs of the equalizer device corresponding to the data packet to generate decoded information corresponding to the data packet. The communication device transmits an acknowledgment packet to acknowledge the data packet such that transmission of the acknowledgment packet begins within required time period, defined by a communication protocol, after an end of the data packet.

In some embodiments, a bandwidth constrained equalized transport (BCET) communication system comprises a transmitter that transmits a signal, a communication channel that transports the signal, and a receiver that receives the signal. The transmitter can comprise a pulse-shaping filter that intentionally introduces memory into the signal, and an error control code encoder that is a low-density parity-check (LDPC) error control code encoder. The error control encoder comprises code that is optimized based on the intentionally introduced memory into the signal, a code rate, a signal-to-noise ratio, and an equalizer structure in the receiver. In some embodiments, the communication system is bandwidth constrained, and the transmitted signal comprises an information rate that is higher than for an equivalent system without intentional introduction of the memory at the transmitter.

A method and system for selecting a symbol detector are herein provided. A method includes extracting a first set of features for a k-th resource element (RE), where k is an integer greater than one, extracting a second set of features from a first RE to a (k1)th RE, and selecting a symbol detector for the k-th RE using a reinforcement learning (RL) neural network based on the extracted first set of features and the extracted second set of features.

Apparatuses, systems, and methods are disclosed for stochastic linear detection. A digital signal processor determines information about a plurality of transmitted signals based on a plurality of received signals. An initialization module determines an estimator matrix and a noise shaping matrix based on channel state information that relates the transmitted signals to the received signals. A sample generation module stochastically generates a plurality of signal estimates so that each signal estimate is a sum of a fixed component and a random component. The fixed component may be based on applying the estimator matrix to a vector of the received signals, and the random component may be based on applying the noise shaping matrix to generated noise. An output module sends soft information to an error-correcting code (ECC) decoder for decoding bits carried by the transmitted signals. The soft information may be based on the plurality of signal estimates.

Pre-charging two or more sets of nodes to set a differential output of a multi-input summation latch connected to the two or more sets of nodes in a pre-charged state, the two or more sets of nodes comprising a set of data signal nodes and a set of DFE correction nodes, in response to a sampling clock, generating a differential data voltage and an aggregate differential DFE correction signal, and generating a data decision by driving the differential output of the multi-input summation latch into one of two possible output states according to a summation of the differential data voltage signal and the aggregate differential DFE correction signal and subsequently holding the data decision by holding the differential output of the multi-input summation latch in a latched state for a duration determined by the sampling clock.

Apparatus, methods, and computer-readable media for adaptive hybrid precoder selection in 2D antenna configurations are disclosed herein. An example method of wireless communication at a UE includes estimating a channel based on CSI-RS received on each port of a plurality of CSI-RS ports from a base station. The example method includes determining, based on the channel estimation, whether to perform disjoint PMI processing or joint PMI processing when determining a first component of a PMI. The example, method includes determining the first component of the PMI based on the determined disjoint PMI processing or joint PMI processing.

A reception device includes: a reception unit receiving transmission signals; a splitting unit splitting received signals into real component and imaginary component; a narrowing unit narrowing down possible signal point candidates of real component of the signal and imaginary component of the signal to signal point candidates based on the real component and the imaginary component of the split received signal; a signal point candidate hypothesizing unit hypothesizing one signal point candidate of real component from the signal point candidates of real component obtained by narrowing-down and hypothesizing one signal point candidate of imaginary component from the signal point candidates of imaginary component obtained by narrowing-down; and a signal estimation value calculating unit estimating real component of the signal based on the one hypothesized real component signal point candidate and estimating imaginary component of the signal based on the one hypothesized imaginary component signal point candidate.