Zhao Yu-Feng, Cao Yu-Jian, Ji Yong, Dai Xu-Chu. Modulation Identification for Single-channel Mixed Communication Signals Based on Cyclic Frequency Features[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1202-1208. doi: 10.3724/SP.J.1146.2013.00454
Citation:
Zhao Yu-Feng, Cao Yu-Jian, Ji Yong, Dai Xu-Chu. Modulation Identification for Single-channel Mixed Communication Signals Based on Cyclic Frequency Features[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1202-1208. doi: 10.3724/SP.J.1146.2013.00454
Zhao Yu-Feng, Cao Yu-Jian, Ji Yong, Dai Xu-Chu. Modulation Identification for Single-channel Mixed Communication Signals Based on Cyclic Frequency Features[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1202-1208. doi: 10.3724/SP.J.1146.2013.00454
Citation:
Zhao Yu-Feng, Cao Yu-Jian, Ji Yong, Dai Xu-Chu. Modulation Identification for Single-channel Mixed Communication Signals Based on Cyclic Frequency Features[J]. Journal of Electronics & Information Technology, 2014, 36(5): 1202-1208. doi: 10.3724/SP.J.1146.2013.00454
Single-channel blind separation of several time-frequency overlapping communication signals, which has potential and wide application, is a hot and intractable point in the field of communication signal processing. The modulation type and source number are necessary for blind separation of several mixed signals received by single channel. In this paper, cycle frequencies of second-order and fourth-order cyclic cumulants of digital modulation signals are investigated. Based on the features of cycle frequencies, a novel method for modulation identification and source number estimation is proposed for single-channel mixed communication signals, and an algorithm is presented. The proposed approach does not need the prior information such as power, carrier frequency, symbol rate, time recovery and so on, and can effectively identify the source number and modulation type of each source when the signal received by single channel is a random mixture of several kinds of typical communication signals (BPSK, QPSK, OQPSK, MSK etc.). Through simulations under different conditions, the performance of the proposed algorithm is examined, and its effectiveness is also demonstrated.