基于FABA-SISO的时变频率选择性衰落信道CPM信号盲均衡

该文针对时变频率选择性衰落信道下高阶连续相位调制(CPM)信号盲均衡中存在的均衡性能较差、复杂度较高以及收敛速度慢等问题，从双向自适应信道均衡的角度出发，将线性调制信号均衡中使用的前后向自适应软输入软输出(FABA-SISO)算法推广，建立一种新的基于FABA-SISO的信道盲均衡方法，并结合逐幸存处理(PSP)思想和Kalman滤波，提出一种适用于高阶CPM信号的自适应盲均衡算法。该算法通过使用FABA-SISO算法，同时利用过去、现在和将来的观察数据进行Kalman滤波信道估计，有效改善了信道估计的精度，同时使用PSP算法来降低系统的复杂度，使得算法具有较好的工程应用性。仿真结果表明所提算法具有良好的盲均衡性能以及收敛性。

Blind Equalization Based on FABA-SISO for Continuous Phase Modulation Signals over Time-varying Frequency-selective Fading Channels

To solve the issues of the high complexity, poor performance, and slow convergence speed in the blind equalization of high order Continuous Phase Modulation (CPM) signals, a new blind equalization method based on Forward Adaptive Backward Adaptive Soft-Input Soft-Output (FABA-SISO) algorithm used in linear modulation signals is developed from the perspective of bidirectional adaptive channel equalization. A novel adaptive blind equalization algorithm for high order CPM signals is proposed based on the combination of Per-Survivor Processing (PSP) and Kalman filtering. The algorithm improves the equalization performance by applying the FABA-SISO which uses the past, the present and the future observation to implement Kalman filtering channel estimation. Simultaneously, a PSP algorithm is used for further improvement of the system complexity, so that the algorithm is better suitable for engineering application. The simulation results show that the proposed algorithm provides a good blind equalization performance and convergence.