Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

A method of OFDM signal detection based on rnn neural network

A technology of signal detection and neural network, which is applied in the field of OFDM signal detection based on RNN neural network, can solve the problems such as the decrease of OFDM signal detection accuracy, achieve the effect of solving the problem of signal reception and improving the performance of spectrum detection

Active Publication Date: 2021-07-20
SHANDONG UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problem that the accuracy of OFDM signal detection decreases due to narrowband interference and noise in OFDM transmission technology applied to CR spectrum sensing, the present invention provides an OFDM signal detection method based on RNN neural network for OFDM transmission technology based on deep learning, Use the powerful learning and memory ability of RNN neural network to complete signal detection

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
  • A method of OFDM signal detection based on rnn neural network
  • A method of OFDM signal detection based on rnn neural network
  • A method of OFDM signal detection based on rnn neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention:

[0029] As can be seen from the accompanying drawings, the OFDM signal detection method based on the RNN neural network in this specific embodiment, the overall model structure of the RNN neural network detection model is as follows figure 1 As shown, the steps are as follows:

[0030] Step 1: Build the OFDM system framework.

[0031] OFDM symbols can be expressed as:

[0032]

[0033] In the formula, t s ≤t≤t s +T, N is the number of sub-channels, T is the OFDM symbol width, d i (i=1,...,N-1) is the data symbol of the subchannel, f c is the carrier frequency, at time t=t s start.

[0034] In the published literature, the mathematical expression of the equivalent baseband signal describing the OFDM output signal is:

[0035]

[0036] In the formula,...

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 discloses an OFDM signal detection method based on an RNN neural network, which can be applied to the cognitive radio spectrum sensing technology of wireless mobile communication, effectively improves the recovery ability of the OFDM system in the aspect of receiver signal demodulation, thereby improving cognition Signal detection performance for radio spectrum sensing. On the basis of analyzing the OFDM system, the present invention first builds the framework of the OFDM system, and uses the framework of the OFDM system to generate a time series data set for model learning. Then, the time series signal data set is learned through the LSTM model of the RNN neural network, and the Adam training algorithm is used to quickly optimize the parameters and the small batch training method to realize the end-to-end spectrum signal detection, which effectively solves the OFDM with NBI and ICI The problem of system signal reception has been improved, and the spectrum detection performance of the system has been improved.

Description

technical field [0001] The invention relates to the technical field of wireless mobile communication, in particular to an OFDM signal detection method based on an RNN neural network. Background technique [0002] The continuous innovation of wireless communication technology makes the transmission of information faster and more reliable. Recently, OFDM technology, as a key technology in wireless communication, plays an important role in promoting the rapid flow of data streams. OFDM technology converts the serial transmission of data streams into parallel transmission through orthogonal subcarriers, which is very good at coping with selective fading and narrowband interference (NBI); at the same time, it adds cyclic prefix (CP) to fight against intersymbol interference (ISI) and inter-carrier interference (ICI) have better performance. In cognitive radio (CR), OFDM technology is also the preferred technology for CR transmission. [0003] Although OFDM technology has many ...

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 Patents(China)
IPC IPC(8): H04L27/26H04L25/02H04L25/03G06N3/04G06N3/08
CPCH04L27/2626H04L27/2647H04L25/0224H04L25/03006G06N3/049G06N3/08G06N3/084G06N3/045
Inventor 何波
Owner SHANDONG 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
Eureka Blog
Learn More
PatSnap group products