Automatic digital modulation recognition based on euclidean distance in hyperspace

作者:Li, Ji*; He, Chen; Chen, Jie; Wang, Dongjian
来源:IEICE - Transactions on Communications, 2006, E89B(8): 2245-2248.
DOI:10.1093/ietcom/e89-b.8.2245

摘要

The recognition vector of the decision-theoretic approach and that of cumulant-based classification are combined to compose a higher dimension hyperspace to get the benefits of both methods. The method proposed in this paper can cover more kinds of signals including signals with order higher than 4 in the AWGN channel even under low SNR values, i.e. those down to -5 dB. The composed vector is input into an RBF neural network to get more reasonable reference points. Eleven kinds of signals, say 2ASK, 4ASK, 8ASK, 2PSK, 4PSK, 8PSK, 2FSK 4FSK, 8FSK, 16QAM and 64QAM, are involved in the discussion.