基于双调整因子的梯度平均盲干扰抑制算法

ABAG-MOE Blind Interference Suppression Algorithm Based on Double Factors

针对采用直接扩频体制的移动卫星系统,提出了一种同时抑制窄带和多址干扰的盲自适应干扰抑制ABAG-MOE算法,该算法在对随机梯度进行统计平均的基础上,引入自调整的步长和遗忘因子,克服了MOE类算法性能受接收矩阵条件数影响的缺点,改善了输出信噪比和信道跟踪能力;文中分析了该算法的运算复杂度,推导证明了算法收敛性的解析性能。静态和动态干扰环境下的仿真表明:算法在保持O(N)运算复杂度的前提下,表现出较好的输出信噪比和信道鲁棒性,具有一定的应用价值。

A low complex ABAG-MOE（Auto-blind adaptive gradient-minimal output energy） algorithm is presented for restraining both MAI and NBI interferences. Based on the averaged stochastic gradient theory, the algorithm brings in a self-tuning regulator for the forgetting and step factors. The algorithm overcomes the defect of MOE affected by the received data matrix. The result proves that ABAG-MOE algorithm has identical convergence properties and the computational cost similar in the least mean square algorithm compared ABAG-MOE algorithm with the blind RLS and LMS schemes.