Self-interference Digital Cancellation Algorithm in Simultaneous Transceiver System Based on Deep Neural Network

JIANG Yilin; WANG Linsen; LI Jinxin

doi:10.11999/JEIT211103

Volume 44 Issue 12

Dec. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(12): 4229-4237

JIANG Yilin, WANG Linsen, LI Jinxin. Self-interference Digital Cancellation Algorithm in Simultaneous Transceiver System Based on Deep Neural Network[J]. Journal of Electronics & Information Technology, 2022, 44(12): 4229-4237. doi: 10.11999/JEIT211103

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JIANG Yilin, WANG Linsen, LI Jinxin. Self-interference Digital Cancellation Algorithm in Simultaneous Transceiver System Based on Deep Neural Network[J]. Journal of Electronics & Information Technology, 2022, 44(12): 4229-4237. doi: 10.11999/JEIT211103

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Self-interference Digital Cancellation Algorithm in Simultaneous Transceiver System Based on Deep Neural Network

doi: 10.11999/JEIT211103

JIANG Yilin^{1, 2},
WANG Linsen¹,
LI Jinxin^{1, 2
,
,}

1.
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2.
Key Laboratory of Advanced Marine Communication and Information Technology, Ministry of Industry and Information Technology, Harbin 150001, China

Funds: Key Projects of National Defense Basic Scientific Research (JCKY2017203B060)

Received Date: 2021-10-11
Rev Recd Date: 2022-06-12

Available Online: 2022-06-21

Publish Date: 2022-12-16

Abstract

Abstract

In order to solve the problem that the self-interference is difficult to eliminate in the transceiver system of the repeater jammer, a self-interference cancellation algorithm based on Deep Neural Network(DNN) is presented in this paper. This proposed algorithm can effectively eliminate the self-interference signal when the self-interference signal is correlated and mixed with the target signal. On this basis, the interference generation method of segmenting interception is used in this paper, which verifies the feasibility of jamming signal cancellation in the simultaneous transceiver system. It realizes the construction of radar jamming signal considering the pulse, which can quickly respond to enemy radars and occupy a favorable position in electronic countermeasures. In this paper, a typical Linear Frequency Modulation(LFM) and Binary Phase Shift Keying (BPSK) radar signal are used to generate a data set to train the DNN network, and the test set is used to test the output model of the network. The experimental results show that the self-interference cancellation algorithm based on DNN can effectively eliminate the self-interference signal when the target signal and self-interference signal are mixed in the simultaneous transceiver system, and the cancellation ratio can reach more than 26 dB when the signal to interference ratio is –8 dB.
- Simultaneous transceiver system,
- Deep Neural Network(DNN),
- Digital cancellation,
- Self-interference

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References(17)

References

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