OFDM signal detection method 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: 2020-10-30
SHANDONG UNIV
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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 pro...

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  • OFDM signal detection method based on RNN neural network
  • OFDM signal detection method based on RNN neural network
  • OFDM signal detection method based on RNN neural network

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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,...

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Abstract

The invention discloses an OFDM signal detection method based on an RNN neural network, which can be applied to a cognitive radio spectrum sensing technology of wireless mobile communication, and effectively improves the recovery capability of an OFDM system in the aspect of receiver signal demodulation, thereby improving the signal detection performance of cognitive radio spectrum sensing. On thebasis of analyzing an OFDM system, firstly, an OFDM system framework is built, and a time sequence data set for model learning is generated by utilizing the OFDM system framework; then, the time sequence signal data set is learned through an LSTM model of the RNN neural network; an Adam training algorithm is adopted to quickly optimize parameters and a small-batch training mode, so that end-to-end spectrum signal detection is realized, the problem of signal receiving of an OFDM system with NBI and ICI is effectively solved, and the spectrum detection performance of the system is 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 ...

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Application Information

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IPC IPC(8): H04L27/26H04L25/02H04L25/03G06N3/04G06N3/08
CPCH04L27/2626H04L27/2647H04L25/0224H04L25/03006G06N3/049G06N3/08G06N3/084G06N3/045
Inventor 何波
Owner SHANDONG UNIV
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