TY - GEN
T1 - MSOM based automatic modulation recognition and demodulation
AU - Zhou, Lei
AU - Cai, Qiao
AU - He, Fangming
AU - Man, Hong
PY - 2011
Y1 - 2011
N2 - Automatic modulation recognition (AMR) and demodulation are two essential components in cognitive radio receivers. This paper proposes a novel method based on MSOM neural networks to automatically recognize the modulation type and demodulate the radio signal at the same time. This efficient method is directly applied to the normalized radio signal samples and has relatively low computation complexity. A dynamic AMR method is also introduced, which further can reduce the computation without obvious loss in recognition. In this paper, four modulation types, i.e. BPSK, MSK, 2FSK and QPSK, are investigated. Our simulation results show that, compared with the traditional cyclic feature-based methods, the proposed MSOM classifier has better performance while requiring less number of signal samples, and it can also perform demodulation at good accuracy.
AB - Automatic modulation recognition (AMR) and demodulation are two essential components in cognitive radio receivers. This paper proposes a novel method based on MSOM neural networks to automatically recognize the modulation type and demodulate the radio signal at the same time. This efficient method is directly applied to the normalized radio signal samples and has relatively low computation complexity. A dynamic AMR method is also introduced, which further can reduce the computation without obvious loss in recognition. In this paper, four modulation types, i.e. BPSK, MSK, 2FSK and QPSK, are investigated. Our simulation results show that, compared with the traditional cyclic feature-based methods, the proposed MSOM classifier has better performance while requiring less number of signal samples, and it can also perform demodulation at good accuracy.
KW - SOM neural network
KW - cognitive radio
KW - demodultation
KW - modulation recognition
UR - http://www.scopus.com/inward/record.url?scp=79959936145&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79959936145&partnerID=8YFLogxK
U2 - 10.1109/SARNOF.2011.5876460
DO - 10.1109/SARNOF.2011.5876460
M3 - Conference contribution
AN - SCOPUS:79959936145
SN - 9781612846811
T3 - 2011 34th IEEE Sarnoff Symposium, SARNOFF 2011
BT - 2011 34th IEEE Sarnoff Symposium, SARNOFF 2011
T2 - 2011 34th IEEE Sarnoff Symposium, SARNOFF 2011
Y2 - 3 May 2011 through 4 May 2011
ER -