Abstract
Considering the problem of EBPSK signal demodulation, a new approach based on the wavelet scalogram using continuous wavelet transform is proposed. Our system is twofold: an adaptive wavelet construction method that replaces manual selection existing wavelets method and, on the other hand, a nonlinear demodulation system based on image processing and pattern classification is proposed. To evaluate the performance of the adaptive wavelet and compare the performance of the proposed system with the existing systems, a series of comprehensive simulation experiments is conducted under the environment of uniform white noise, colored noise, and additive white Gaussian noise channel, respectively. Simulation results of different wavelets show that the system using adaptive wavelet has lower bit error rate (BER). Moreover, simulation results of several systems show that the BER of the proposed system is the lowest among all systems, such as amplitude detection, integral detection, and some continuous wavelet transform systems (specific scales and times and maximum lines). In a word, the adaptive wavelet construction proposed in this paper yields superior performances compared with the manual selection, and the proposed system has better performances than the existing systems. Index terms are signal demodulation, adaptive wavelet, continuous wavelet transform, and BER.
Highlights
Spectrum shortage has been a focus of concern in the field of communications
The computational complexity of all studied systems is shown in Table 1. n is the length of code, from which we see that ID and AD’s asymptotical complexity is proportional with the parameter n and the complexity of maximum lines (ML), scales and times (SST), and the proposed system using manual selection wavelets is the same as the complexity of the proposed system using adaptive wavelet
ML, SST, and the proposed system adopting manual selection wavelets have the same complexity as the proposed method, while their bit error rate (BER) are higher than the proposed method, which can be seen in Figures 6 and 7
Summary
Spectrum shortage has been a focus of concern in the field of communications. In order to meet the increasing demand for communication systems, the research on bandwidth efficient modulations is extremely urgent. A special impacting filter (SIF), which can produce high impact at the phase jumping point, constrict bandwidth, and extend channel capacity is applied in the demodulator [5]. Introducing wavelet transform in demodulation system can achieve great results. Image processing methods are always introduced to deal with CWT scalogram, such as feature selection and background subtraction, which can be seen in [10,11,12]. Wavelet transform is a common method for image processing [13, 14]. Wavelet theory has been widely used to analyze, evaluate, pick, and detect signals [15,16,17,18]
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