Digital Modulation Classification via Sequential Monte Carlo for Frequency-Nonselective Fading MIMO Channels
非频率选择性衰落MIMO信道上基于序列蒙特卡罗的数字调制识别方法

A modulation classification method for phase-amplitude-modulated signals transmitted through frequency-nonselective fading Multi-Input Multi-Output (MIMO) channels is presented based on Sequential Monte Carlo (SMC) method. An equivalent dynamic state space model is first derived from the MIMO channel. Then the probabilities of all possible modulation types of different transmit antennas can be calculated by sequential importance sampling and type-move step. Finally, noise average is realized utilizing the un-correlation of transmitted data symbols over N channel observation lengths. Moreover, modulations classification is achieved along with estimation of transmitted data symbols. The complexity of the proposed method is linear with the observation channel lengths, number of transmit antennas, sample size, and cardinality of modulation constellation. Simulations show that the proposed method performs well on various constellations.