Sub-Nyquist Sampling of BPSK Signals via Feedback Structure

We consider the problem of sampling binary phase shift keying (BPSK) signals, which are widely used in communications and radar systems. Although sub-Nyquist sampling of such signals has been treated in various works, giant samples were needed. In this brief, a new sub-Nyquist sampling method based on a multichannel feedback structure is proposed for BPSK signals, which requires fewer samples. BPSK signals can be characterized by a finite number of parameters, namely, the carrier frequency, amplitude, locations of discontinuities, and phase of each symbol. Our feedback structure consists of a main channel and a feedback channel. The carrier frequency and amplitude can be estimated by the estimation of signal parameters by a rotational invariance technique algorithm in the main channel, while the phases and locations of discontinuities can be estimated by the annihilating filter in the feedback channel. The effectiveness of the proposed method is verified via simulations. In a noiseless situation, for a seven-segment BPSK signal lasting $1~{\mu } {s}$ with a 500-MHz carrier frequency, the equivalent sampling rate of the proposed method is only 3.8% of the carrier frequency, and much less than the Nyquist sampling rate of the signal. Finally, we analyze the effect of noise and present a robust reconstruction algorithm. Simulation results show that the proposed method exhibits better noise robustness than previous approaches.

[1]  Guan Gui,et al.  Frequency estimation of cyclic spectrum carrier based on compressive sampling of BPSK signal , 2015 .

[2]  X. Jun,et al.  The improvement of symbol rate estimation by the wavelet transform , 2005, Proceedings. 2005 International Conference on Communications, Circuits and Systems, 2005..

[3]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[4]  E.J. Candes Compressive Sampling , 2022 .

[5]  Xianci Xiao,et al.  Carrier frequency and chip rate estimation based on cyclic spectral density of MPSK signals , 2004, 2004 International Conference on Communications, Circuits and Systems (IEEE Cat. No.04EX914).

[6]  V. John Mathews,et al.  A Likelihood-Based Algorithm for Blind Identification of QAM and PSK Signals , 2018, IEEE Transactions on Wireless Communications.

[7]  James A. Cadzow,et al.  Signal enhancement-a composite property mapping algorithm , 1988, IEEE Trans. Acoust. Speech Signal Process..

[8]  Ning Fu,et al.  A Simplified FRI Sampling System for Pulse Streams Based on Constraint Random Modulation , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[9]  Thierry Blu,et al.  Sampling Piecewise Sinusoidal Signals With Finite Rate of Innovation Methods , 2010, IEEE Transactions on Signal Processing.

[10]  Franco Mazzenga,et al.  Blind least-squares estimation of carrier phase, Doppler shift, and Doppler rate for m-PSK burst transmission , 1998, IEEE Communications Letters.

[11]  Zhengguang Xu,et al.  Direction Finding of BPSK Signals Using Time-Modulated Array , 2018, IEEE Microwave and Wireless Components Letters.

[12]  Thierry Blu,et al.  Sampling signals with finite rate of innovation , 2002, IEEE Trans. Signal Process..

[13]  Ching-Che Chung,et al.  A Symbol-Rate Timing Synchronization Method for Low Power Wireless OFDM Systems , 2008, IEEE Transactions on Circuits and Systems II: Express Briefs.

[14]  Jelena Kovačević,et al.  Rakeness-Based Compressed Sensing of Multiple-Graph Signals for IoT Applications , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[15]  Michael B. Wakin,et al.  CHOCS: a framework for estimating compressive higher order cyclostationary statistics , 2012, Defense + Commercial Sensing.

[16]  Tariq S. Durrani,et al.  Blind estimation of frequency offset in the presence of unknown multipath , 2000, 2000 IEEE International Conference on Personal Wireless Communications. Conference Proceedings (Cat. No.00TH8488).

[17]  Yang Xinquan,et al.  Research on parameter estimation of MPSK signals based on the generalized second-order cyclic spectrum , 2014, 2014 XXXIth URSI General Assembly and Scientific Symposium (URSI GASS).

[18]  Andrew J. Viterbi,et al.  Nonlinear estimation of PSK-modulated carrier phase with application to burst digital transmission , 1983, IEEE Trans. Inf. Theory.

[19]  Jianhua Lu,et al.  A symbol rate estimation algorithm based on Morlet wavelet transform and autocorrelation , 2009, 2009 IEEE Youth Conference on Information, Computing and Telecommunication.