In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shi...In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shift and complex multipath channel conditions,extracting discriminative features from high-order modulation signals and ensuring model inter-pretability remain challenging.To address these issues,this paper proposes a Fourier attention net-work(FAttNet),which combines an attention mechanism with a Fourier analysis network(FAN).Specifically,the method directly converts the input signal to the frequency domain using the FAN,thereby obtaining frequency features that reflect the periodic variations in amplitude and phase.Abuilt-in attention mechanism then automatically calculates the weights for each frequency band,focusing on the most discriminative components.This approach improves both classification accu-racy and model interpretability.Experimental validation was conducted via high-order modulationsimulation using an RF testbed.The results show that under three different Doppler frequencyshifts and complex multipath channel conditions,with a signal-to-noise ratio of 10 dB,the classifi-cation accuracy can reach 89.1%,90.4%and 90%,all of which are superior to the current main-stream methods.The proposed approach offers practical value for dynamic spectrum access and sig-nal security detection,and it makes important theoretical contributions to the application of deeplearning in complex electromagnetic signal recognition.展开更多
To increase the spectral efficiency of the underwater acoustic(UWA)communication system,the high order quadrature amplitude modulations(QAM)are deployed.Recently,the prob-abilistic constellation shaping(PCS)has been a...To increase the spectral efficiency of the underwater acoustic(UWA)communication system,the high order quadrature amplitude modulations(QAM)are deployed.Recently,the prob-abilistic constellation shaping(PCS)has been a novel technology to improve the spectral efficiency.The PCS with high-order QAM is introduced into the UWA communication system.A turbo equal-ization scheme with PCS was proposed to cancel the severe inter-symbol interference(ISI).The non-zero a priori information is available for the equalizer and decoder before turbo iteration.A pri-ori hard decision approach is proposed to improve the detection performance and the equalizer con-vergence speed.At the initial turbo iteration,the relation between the a priori information and the probability of the amplitude of 16QAM symbols in one dimension is given.The simulation results verified the efficiency of the proposed method,and compared to the uniform distribution(UD),the PCS-16QAM had a significant improvement of the bit error rate(BER)performance with PCS-ad-aptive turbo equalization(PCS-ATEQ).The UWA communication experiments further verified the performance superiority of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China(No.62027801).
文摘In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shift and complex multipath channel conditions,extracting discriminative features from high-order modulation signals and ensuring model inter-pretability remain challenging.To address these issues,this paper proposes a Fourier attention net-work(FAttNet),which combines an attention mechanism with a Fourier analysis network(FAN).Specifically,the method directly converts the input signal to the frequency domain using the FAN,thereby obtaining frequency features that reflect the periodic variations in amplitude and phase.Abuilt-in attention mechanism then automatically calculates the weights for each frequency band,focusing on the most discriminative components.This approach improves both classification accu-racy and model interpretability.Experimental validation was conducted via high-order modulationsimulation using an RF testbed.The results show that under three different Doppler frequencyshifts and complex multipath channel conditions,with a signal-to-noise ratio of 10 dB,the classifi-cation accuracy can reach 89.1%,90.4%and 90%,all of which are superior to the current main-stream methods.The proposed approach offers practical value for dynamic spectrum access and sig-nal security detection,and it makes important theoretical contributions to the application of deeplearning in complex electromagnetic signal recognition.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA22030101)the National Natural Science Foundation of China(No.61971472)the Institute of Acoustics,Chinese Academy of Sciences Free Exploration Project(No.ZYTS202003).
文摘To increase the spectral efficiency of the underwater acoustic(UWA)communication system,the high order quadrature amplitude modulations(QAM)are deployed.Recently,the prob-abilistic constellation shaping(PCS)has been a novel technology to improve the spectral efficiency.The PCS with high-order QAM is introduced into the UWA communication system.A turbo equal-ization scheme with PCS was proposed to cancel the severe inter-symbol interference(ISI).The non-zero a priori information is available for the equalizer and decoder before turbo iteration.A pri-ori hard decision approach is proposed to improve the detection performance and the equalizer con-vergence speed.At the initial turbo iteration,the relation between the a priori information and the probability of the amplitude of 16QAM symbols in one dimension is given.The simulation results verified the efficiency of the proposed method,and compared to the uniform distribution(UD),the PCS-16QAM had a significant improvement of the bit error rate(BER)performance with PCS-ad-aptive turbo equalization(PCS-ATEQ).The UWA communication experiments further verified the performance superiority of the proposed method.
