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Ofdm channel estimation method based on deep learning

A channel estimation and deep learning technology, applied in baseband systems, baseband system components, digital transmission systems, etc., can solve problems such as not taking into account the time-varying characteristics of fast fading channels and difficult to apply, to achieve small estimation errors and improve quality , Improve the effect of channel estimation quality

Active Publication Date: 2021-08-27
XIDIAN UNIV
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Problems solved by technology

However, this scheme uses a block pilot pattern, which is suitable for slow fading channels, and does not take into account the time-varying characteristics of fast fading channels.
Therefore, in the application scenario of fast fading channel, this scheme is difficult to apply

Method used

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  • Ofdm channel estimation method based on deep learning
  • Ofdm channel estimation method based on deep learning
  • Ofdm channel estimation method based on deep learning

Examples

Experimental program
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Effect test

Embodiment 1

[0042] The OFDM communication system in this example uses a comb pilot pattern, such as figure 2 As shown, the number of subcarriers is set to N c , the transmitter inserts pilots at equal intervals, and the interval is set to D P , the channel changes rapidly, and only one antenna is used at the transmitter and receiver.

[0043] Step 1. The receiving end obtains the received signal y in the time domain and performs preprocessing to obtain the received signal Y in the frequency domain at the pilot position P .

[0044] 1a) The receiving end obtains the received signal y in the time domain, removes the cyclic prefix CP, and performs the discrete Fourier transform DFT on y in order to obtain the received signal in the frequency domain where C represents the set of complex numbers, N c is the number of subcarriers, and the received signal Y in the frequency domain contains the information Y of the pilot position P and data location information Y D ;

[0045] 1b) Let the...

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Abstract

The invention discloses an OFDM channel estimation method based on deep learning, which mainly solves the problems of poor channel estimation quality or high implementation complexity in the prior art. The scheme is: at the receiving end, obtain the time domain signal y and perform preprocessing to obtain the frequency domain signal Y of the pilot position of the received signal P ; Use the fully connected layer neural network to build the channel estimation model CE‑Net and train it; use the data in the real environment for migration training; place CE‑Net at the receiving end for online channel estimation. The invention reduces the implementation complexity of channel estimation, remarkably improves the quality of channel estimation, and can be used in OFDM communication system under comb pilot mode.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a channel estimation method in an OFDM system, which can be used in an OFDM communication system based on a comb pilot. Background technique [0002] OFDM is one of the key technologies widely used in current communication systems. It has low implementation complexity and can effectively improve frequency band utilization. In broadband mobile communication systems, wireless channels usually have frequency selectivity and time-varying characteristics, and the performance of channel estimation will directly affect the quality of received signals. Therefore, it is necessary to perform dynamic channel estimation and ensure the accuracy of estimation results. [0003] Considering the pilot-based OFDM channel estimation widely used at present, when the OFDM system chooses the comb pilot mode, the channel estimation can be divided into channel estimation and channel in...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L25/02H04L27/26
CPCH04L25/0224H04L25/0254H04L27/2695
Inventor 高明廖覃明李靖潘毅恒黄凤杰
Owner XIDIAN UNIV
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