Abstract
With the challenges of the unknown noise and time-varying channel, a new modulation recognition algorithm is proposed in this paper. Firstly, we propose a new dynamic state-space model to describe the sequential modulation recognition problem. And the time-variant fading channel is described by finite state Markov channel. Secondly, based on particle filter technology which can overcome the adverse effects of time-varying noise and sequential Bayesian inference method which can premeditate the dynamic transfer characteristics of the fading channel gain, a new algorithm is proposed to estimate the noise variance, channel state and modulation scheme jointly. The algorithm can raise modulation recognition performance with unknown noise variance in the time-varying channel by simulation.
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