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

该文针对非频率选择性衰落多输入多输出(MIMO)信道提出了一种基于序列蒙特卡罗(SMC)方法的幅度-相位调制方式识别方法。首先将MIMO系统等效为一个动态状态空间模型，然后利用序列重要性采样和模式转移步骤估计每根发送天线采用的各种可能调制方式的概率，最后利用各个信道上发送符号的不相关性在长为N的观测信道上进行噪声平均。该方法能够在识别数字调制方式的同时估计发送数据符号。其复杂度是信道观测长度、发送天线数、采样大小、调制星座大小的线性函数。仿真结果表明提出的数字调制识别方法在各种调制星座上具有良好的性能。

Digital Modulation Classification via Sequential Monte Carlo for Frequency-Nonselective Fading MIMO Channels

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.