基于DNN的无人机数据OFDM传输技术

doi:10.12305/j.issn.1001-506X.2022.02.41

Abstract

Abstract:

The unmmand aerial vehicle (UAV) channel contains multipath, Doppler frequency shift. It is easily affected by external interference and nonlinear distortion caused by high power amplification. To solve those problems a data transmission technology of UAV orthogonal frequency division multiplexing (OFDM) based on deep neural network (DNN) is proposed. In the downlink, OFDM system is used. After demodulation and borrowing at the receiver, the least square (LS) channel estimation and zero forcing (ZF) algorithm are used for preliminary signal detection, and then input into the DNN composed of BiLSTM and full connected layer for channel estimation and signal detection optimization, and data stream recovery. Simulation results show that compared with the traditional interpolation method, the proposed method has obvious advantages in channel estimation performance under three states of UAV takeoff and landing, flight and hovering, and the bit error rate performance is improved by at least one order of magnitude; under the influence of nonlinear distortion and external interference, the proposed method still has significant performance advantages, which not only simplifies the processing module of nonlinear distortion and interference, but also improves the stability of the system qualitative.

Key words: unmanned aerial vehicle (UAV), time varying multipath channel, orthogonal frequency division multiplexing (OFDM), deep neural network (DNN), interference, channel estimation, signal detection

CLC Number:

TN914.34

Buhua LIU, Dan DING, Liu YANG, Naiyang XUE, Zhongqian LIU. OFDM data transmission technology of UAV based on deep neural network[J]. Systems Engineering and Electronics, 2022, 44(2): 696-702.

Figures/Tables 12

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References 27

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	飞行速度/(m/s)	飞行高度/m	多普勒频移/Hz	莱斯因子/dB	时延/μs	能量损失/dB
起飞降落	40	100	320	20	[0, 0.33, 0.66]	[0, -7, -20]
途中飞行	134	750	1 072	15	[0, 2.5, 5]	[0, -7, -15.2]
任务盘旋	40	1 050	320	10	[0, 3.5, 6]	[0, -0.97, -10]

信道状态	SNR
信道状态	0 dB	5 dB	10 dB	15 dB	20 dB	25 dB
起飞降落状态	0.185	0.066	0.013	0.003	0.001	5.0e-4
途中飞行状态	0.190	0.074	0.018	0.005	0.002	0.001
任务盘旋状态	0.218	0.072	0.018	0.004	0.001	6.02e-4

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OFDM data transmission technology of UAV based on deep neural network

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