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Apparatus and method for compensating channel based on artificial neural network

An artificial neural network and channel technology, applied to equipment and fields based on artificial neural network compensation channels, can solve problems such as difficult to accurately estimate channels and errors

Pending Publication Date: 2020-12-18
HYUNDAI MOTOR CO LTD +2
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the WAVE technique specifies the number of subcarriers and pilots suitable for the moving speed of pedestrians, it is difficult to estimate the channel accurately due to the channel variation (high Doppler effect and multipath) caused by the high-speed motion of the vehicle
[0006] Although a data pilot aided (DPA) scheme has been proposed, which estimates the channel of the current Orthogonal Frequency Division Multiplexing (OFDM) symbol by constructing a dummy data pilot signal based on the previous OFDM symbol, as A scheme for estimating a rapidly changing channel in a WAVE V2X communication environment, the DPA channel estimation scheme will cause errors in the demapping process due to the distortion and noise of the estimated channel

Method used

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  • Apparatus and method for compensating channel based on artificial neural network
  • Apparatus and method for compensating channel based on artificial neural network
  • Apparatus and method for compensating channel based on artificial neural network

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Embodiment Construction

[0032] It should be understood that the term "vehicle" or "vehicular" or other similar terms as used herein generally includes motor vehicles, such as passenger vehicles, including sport utility vehicles (SUVs), buses, trucks, various commercial vehicles, Water vehicles including ships of all kinds, aircraft, etc., and including hybrid vehicles, electric vehicles, plug-in hybrid vehicles, hydrogen-powered vehicles and other alternative fuel vehicles (for example, fuels derived from sources other than petroleum) . As referred to herein, a hybrid vehicle is a vehicle that has two or more sources of power, such as a gasoline-powered vehicle and an electric-powered vehicle.

[0033] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise....

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Abstract

An apparatus and method for compensating a channel based on an artificial neural network are provided. The apparatus includes a channel learning device that learns a property of the channel, and a channel compensating device that compensates for an error of the channel based on a learning result of the channel learning device.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of Korean Patent Application No. 10-2019-0071791 filed with the Korean Intellectual Property Office on June 17, 2019, the entire contents of which are hereby incorporated by reference. technical field [0003] The present disclosure relates to techniques for compensating for channel errors (noise, distortion) based on artificial neural networks. Background technique [0004] Vehicle-to-everything (V2X) communication technology is a core technology for providing traffic safety and application services to drivers, because data loss and transmission delay are directly related to driver safety, so it requires high reliability and low latency (HR / LL). [0005] However, the Wireless Access in Vehicular Environment (WAVE) technology based on the IEEE 802.11p physical layer standard is a communication technology that improves the IEEE 802.11a / g wireless LAN technology to be suitable for th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L25/02H04L27/26H04W4/40G06N3/04
CPCH04L25/022H04L27/2688H04W4/40G06N3/045H04W4/44H04W4/46G06N3/088H04L27/2695G06N3/082H04L25/0254H04L25/0224G06N3/04
Inventor 金增一高荣铁丁在勋宋昌翼韩丞镐
Owner HYUNDAI MOTOR CO LTD