Fast and Robust Modulation Classification via Kolmogorov-Smirnov Test

作者：Wang Fanggang^*; Wang Xiaodong

来源：IEEE Transactions on Communications, 2010, 58(8): 2324-2332.

DOI：10.1109/TCOMM.2010.08.090481

• Automatic modulation classification
• Kolmogorov-Smirnov test
• fading
• OFDM
• frequency offset
• non-Gaussian noise

A new approach to modulation classification based on the Kolmogorov-Smirnov (K-S) test is proposed. The K-S test is a non-parametric method to measure the goodness of fit. The basic procedure involves computing the empirical cumulative distribution ECDF) of some decision statistic derived from the received signal, and comparing it with the CDFs or the ECDFs of the signal under each candidate modulation format. The K-S-based modulation classifiers are developed for various channels, including the AWGN channel, the flat-fading channel, the OFDM channel, and the channel with unknown phase and frequency offsets, as well as the non-Gaussian noise channel, for both QAM and PSK modulations. Extensive simulation results demonstrate that compared with the traditional cumulant-based classifiers, the proposed K-S classifiers offer superior classification performance, require less number of signal samples (thus is fast), and is more robust to various channel impairments.

• 出版日期2010-8
• 单位北京邮电大学