Neural network assisted iterative receiving method suitable for high-speed visible light communication

A technology of visible light communication and neural network, applied in the shaping network of the transmitter/receiver, components of the baseband system, multi-frequency code system, etc., can solve the problem of not considering clipping distortion, performance gap, BICM receiver Distortion and other issues

Active Publication Date: 2019-06-14
SOUTHEAST UNIV
View PDF6 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Nevertheless, traditional BICM receivers still suffer from severe distortion, the reason is that the clipping distortion does not take into account the maximum a posteriori soft demodulation process, still adopts the Gaussian distribution as the channel conditional probability, resulting in the logarithm of the mismatch likelihood ratio
For nonlinear distortion scenarios, research institutions have proposed such as maximum likelihood sequence detection BICM receiver (MLSD-BICM), Gaussian mixture model BICM receiver (GMM-BICM), etc., but the performance of the two is still far from the Shannon limit

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Neural network assisted iterative receiving method suitable for high-speed visible light communication
  • Neural network assisted iterative receiving method suitable for high-speed visible light communication
  • Neural network assisted iterative receiving method suitable for high-speed visible light communication

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0031] Such as figure 1 Shown is to verify the performance results of the NN-BICM receiver. It is necessary to build a DCO-OFDM system simulation platform affected by bilateral clipping. The main physical layer parameters are shown in Table 1. The encoding scheme is determined to be the LDPC code of the IEEE 802.11 protocol; the encoding code length is selected according to the number of subcarriers, specifically, the encoding code length corresponding to 64 subcarriers is equal to 1296, and the encoding code length corresponding to 1024 subcarriers is equal to 1944; decoding The algorithm adopts Belief Propagation (BP) algorithm, and the maximum number of decoding iterations is set to 50.

[0032] Such as figure 2 As shown, a neural network-assisted iterative receiving method suitable for high-speed visible light communication is carried out according to the following steps:

[0033] In the S1 step in the embodiment, it should be noted that the modulation order M can be se...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a neural network assisted iterative receiving method suitable for high-speed visible light communication, and aims to correct soft decision information through a neural networkreceiver so as to eliminate the influence of clipping distortion. The neural network BICM receiver comprises: (1) a cost function adopts a cross entropy function; (2) a back propagation algorithm is adopted in the training method; (3) the input layer comprises a real part and an imaginary part for receiving symbols and corresponding Gaussian noise, and the output layer obtains the probability value of each constellation point; and (4) the hidden layer and the output layer respectively adopt a panh function and a softmax function. Compared with an existing clipping enhancement scheme, the method has a more obvious inhibition effect and reasonable algorithm complexity, and DCO-enhancement is facilitated. And the OFDM has robustness for clipping distortion.

Description

technical field [0001] The present invention relates to the field of visible light communication, in particular to a neural network-assisted iterative receiving method suitable for high-speed visible light communication. Background technique [0002] As a supplement to the fifth generation communication system (5G), visible light communication has become a promising indoor short-range communication technology. Visible light communication uses intensity modulation direct detection to drive light-emitting diodes (LEDs), which can realize data communication and indoor lighting at the same time. In recent years, Optical Orthogonal Frequency Division Multiplexing (O-OFDM) has attracted widespread attention due to its higher spectrum utilization and anti-multipath effects. O-OFDM technology includes various candidate schemes such as asymmetric clipped optical OFDM (ACO-OFDM), pulse amplitude modulated discrete multi-tone (PAM-DMT) and DC biased optical OFDM (DCO-OFDM). Compared ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04L27/26H04L27/34H04L25/03
Inventor 赵春明贺渊姜明凌昕彤李骁敏
Owner SOUTHEAST UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap