US 2025/0193058 A1Published application

Communication apparatus, learning apparatus, communication system, control circuit, storage medium, and step size update method

AssigneeMitsubishi Electric Corporation

InventorsManabu SAKAI, Akinori TAIRA

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Abstract

A communication apparatus includes: a linear equalization unit for a reception signal; a tap coefficient adjustment unit that adjusts, based on a step size, a tap coefficient; and a step size learning unit. The step size learning unit includes: a plurality of neural network layers that each perform computation of an updated tap coefficient based on an initial tap coefficient or an updated tap coefficient output from a previous stage, the reception signal, and a reference signal, and each hold an internal parameter; a learning processing unit that performs learning using an error function as a mean square error between a tap coefficient based on the reception signal and the reference signal and an updated tap coefficient from the neural network layer at a last stage, and updates the internal parameters; and an internal parameter collection unit that updates the step size based on the internal parameters.

Claims15

Dependent claims

A communication apparatus comprising:

linear equalization circuitry to perform linear equalization on a reception signal;
tap coefficient adjustment circuitry to adjust, based on a step size, a tap coefficient to be used in the linear equalization;
and
step size learning circuitry to learn the step size, wherein
the step size learning circuitry includes:
a plurality of neural network layers to each perform computation of an updated tap coefficient based on a specified initial tap coefficient or an updated tap coefficient output from the neural network layer at a previous stage, the reception signal, and a reference signal that is a specified signal sequence, and to each hold an internal parameter to be used in the computation;
learning processing circuitry to perform learning using an error function in the learning as a mean square error between a tap coefficient based on a least square solution calculated from the reception signal and the reference signal and an updated tap coefficient output from the neural network layer at a last stage of the plurality of neural network layers, and to update the internal parameters;
and
internal parameter collection circuitry to update the step size based on the internal parameters collected from the plurality of neural network layers.

6 more elements

A learning apparatus comprising:

step size learning circuitry to learn the step size to be used in a communication apparatus to adjust, based on the step size, a tap coefficient to be used in linear equalization and to perform the linear equalization on a reception signal, wherein
the step size learning circuitry includes:
a plurality of neural network layers to each perform computation of an updated tap coefficient based on a specified initial tap coefficient or an updated tap coefficient output from the neural network layer at a previous stage, the reception signal, and a reference signal that is a specified signal sequence, and to each hold an internal parameter to be used in the computation;
learning processing circuitry to perform learning using an error function in the learning as a mean square error between a tap coefficient based on a least square solution calculated from the reception signal and the reference signal and an updated tap coefficient output from the neural network layer at a last stage of the plurality of neural network layers, and to update the internal parameters;
and
internal parameter collection circuitry to update the step size based on the internal parameters collected from the plurality of neural network layers.

3 more elements

Dependencies are inferred from the claim text.