Abstract
In this paper we propose new analogue and digital recognition algorithm to discriminate between 15 signals (amplitude modulation (AM), frequency modulation (FM), double sideband modulation (DSB), lower sideband modulation (LSB), upper sideband modulation (USB), vestigial sideband (VSB), combined (AM–FM), carrier wave (CW), Noise, binary amplitude shift keying (ASK2), ASK4, binary phase shift keying (PSK2), PSK4, binary frequency shift keying (FSK2) and FSK4). Six key features extracted from instantaneous information (amplitude and phase) and signal spectral, are used to fulfill the requirement of this algorithm. Computer simulations for the signals of interest corrupted by band limited Gaussian noise was performed, the simulation results show that the overall recognition rate can reach 99.6 % when the signal to noise ratio (SNR) = 3 dB. This algorithm uses a lesser number of features compared with most of the existing automatic analogue and digital modulation recognition algorithms, thus leading to lower computational load.
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Acknowledgement
The authors would like to acknowledge Sarafadeen of UESTC for his support and contributions towards the accomplishment of this paper. This work was supported in part by the National Natural Science Foundation of China under Grant 11176005.
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Dahap, B.I., HongShu, L., Ramadan, M. (2014). Simple and Efficient Algorithm for Automatic Modulation Recognition for Analogue and Digital Signals. In: Zhang, B., Mu, J., Wang, W., Liang, Q., Pi, Y. (eds) The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 246. Springer, Cham. https://doi.org/10.1007/978-3-319-00536-2_41
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DOI: https://doi.org/10.1007/978-3-319-00536-2_41
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