A wireless network can generate candidate signal configurations for physical transmissions to or from a user equipment (UE) in a radio environment. The generation of candidate signal configurations can be performed using a first neural network that is associated with the UE. These signal configurations can then be evaluated using a second neural network that is associated with the radio environment. The second neural network can be trained using measurements from previous physical transmissions in the radio environment. The trained second neural network generates a reward value that is associated with the candidate signal configurations. The first neural network is then trained using the reward values from the second neural network to produce improved candidate signal configurations. When a signal configuration that produces a suitable reward value is generated, this signal configuration can be used for the physical transmission in the radio environment.

Examples described herein include methods, devices, and systems which may compensate input data for I/Q imbalance or noise related thereto to generate compensated input data. In doing such the above compensation, during an uplink transmission time interval (TTI), a switch path is activated to provide converted input data to a receiver stage including a recurrent neural network (RNN). The RNN may calculate an error representative of the noise based partly on the input signal to be transmitted and a feedback signal to generate filter coefficient data associated with the I/Q imbalance. The feedback signal is provided, after processing through the receiver, to the RNN. During an uplink TTI, the converted input data may also be transmitted as the RF wireless transmission via an RF antenna. During a downlink TTI, the switch path may be deactivated and the receiver stage may receive an additional RF wireless transmission to be processed in the receiver stage.

An apparatus for processing a received radio signal includes at least one processor and at least one memory. The at least one memory storing computer program code. The at least one memory and the computer program code being configured to, with the at least one processor, cause the apparatus to at least in part perform processing (received radio signal data with first and second signal processing chains, which respectively include first and second processing modules configured to respectively determine first output and an estimation of the first output data, and determine second output data using a neural network based on the estimation; updating parameters of the neural network based on the first output data and the second output data; and after the updating, processing the received radio signal data with the second signal processing chain, without applying the first processing module.

A method for performing optical constellation conversion, according to which each received symbol from a constellation of input symbols is optically split into M components and each component is multiplied by a first predetermined different complex weighing factor, to achieve M firstly weighted components with different amplitudes. Then a nonlinear processor optically performs a nonlinear transform on each M firstly weighted components, so as to obtain M outputs which are linearly independent, Finally, a linear processor optically performs a linear transform to obtain a new converted constellation by optically multiplying, in the complex plane, each of the M outputs by a second predetermined different complex weighing factor, to achieve M secondly weighted components and then summing the M secondly weighted components.

A physical layer transceiver for connecting a host device to a wireline channel medium includes a host interface for coupling to the host device, a line interface for coupling to the channel medium, a transmit path operatively coupled to the host interface and the line interface, a receive path operatively coupled to the line interface and the host interface, and adaptive filter circuitry operatively coupled to at least one of the transmit path and the receive path for filtering signals on the at least one of the transmit path and the receive path, the adaptive filter circuitry including a non-linear equalizer. The non-linear equalizer may be a neural network equalizer based on a multi-layer perceptron or a radial-basis function, or may be a linear equalizer with a non-linear activation function. The non-linear equalizer also may have a front-end filter to reduce input complexity.

According to one aspect, an embodiment radio frequency receiver device comprises an input interface configured to receive a radio frequency signal of a given type and convert same into an electric signal, a detector configured to detect at least one voltage level in the electric signal, a pulse generator configured to generate at least one pulse train representative of the voltage levels detected, and a processing unit configured to determine the type of the radio frequency signal from the at least one pulse train.

According to one aspect, an embodiment radio frequency receiver device comprises an input interface configured to receive a radio frequency signal of a given type and convert same into an electric signal, a detector configured to detect at least one voltage level in the electric signal, a pulse generator configured to generate at least one pulse train representative of the voltage levels detected, and a processing unit configured to determine the type of the radio frequency signal from the at least one pulse train.

A filter bank multi-carrier (FBMC)-offset quadrature amplitude modulation (OQAM) system is disclosed. The FBMC-OQAM system includes a processing circuitry which is configured to receive a signal over a transmission medium, equalize the signal by a convolution neural network (CNN) equalizer, wherein the CNN equalizer is configured to estimate the received signal without performing channel estimation, and output the estimated signal as a bit stream.

Various embodiments may employ neural networks at transmitting devices to compress transmit (TX) waveform distortion. In various embodiments, compressed TX waveform distortion information may be conveyed to a receiving device. In various embodiments, the signaling of TX waveform distortion information from a transmitting device to a receiving device may enable a receiving device to mitigate waveform distortion in a transmit waveform received from the transmitting device. Various embodiments include systems and methods of wireless communication by transmitting a waveform to a receiving device performed by a processor of a transmitting device. Various embodiments include systems and methods of wireless communication by receiving a waveform from a transmitting device performed by a processor of a receiving device.

A signal transmission apparatus (1) includes: a distortion compensation unit (11) for performing a distortion compensation processing on an input signal (x) by using a Neural Network (112) including L+1 arithmetic layers that include L (L is a variable number representing an integer equal to or larger than 1) hidden layer (112M) and an output layer (112O); a storage unit (13) for storing parameter sets (131) each of which includes a parameter for Q (Q is a variable number representing an integer equal to or smaller than L) arithmetic layer of the L+1 arithmetic layers; and an application unit (142) for selecting one parameter set from the parameter sets based on a signal pattern of the input signal and applying the parameter included in the selected one parameter set to the M number of arithmetic layer, a parameter of another arithmetic layer of the L+1 arithmetic layers, which is other than the Q arithmetic layer, is fixed.