【摘要】 针对短波信道以及短波瞬间通信以帧为单位进行传输的特点,提出了一种新的复合型自适应Turbo均衡算法(CATEA)。该算法结合最小均方(LMS)算法和递归最小平方(RLS)均衡算法的优点,分别在训练和直接判决阶段调整均衡器参数,因而克服了LMS算法收敛慢以及RLS算法计算量大的缺点。通过将该均衡算法与Viterbi译码算法进行迭代均衡和译码,极大地提高了均衡器性能,同时保持了较低的复杂性。仿真和实验测试证明了该算法的有效性。更多还原

【Abstract】 A novel combined adaptive Turbo equalization algorithm (CATEA) based on the characteristics of high frequency (HF) channel and HF burst communication is presented. With the merits of LMS and RLS algorithms, the algorithm adaptively adjusts equalizer tap coefficients respectively in training and direct decision-making phases, thus overcoming the disadvantages of LMS and RLS equalization algorithms. Through iterative equalization and decoding between CATEA and Viterbi, it improves the performance of the equalizer and maintains low complexity. The simulation and experimental tests demonstrate the validity of this algorithm.更多还原