论文部分内容阅读
针对常数模和判决引导双模式盲均衡算法切换时机选择困难问题,提出了一种并联滤波的双模式融合盲均衡算法。算法以并联滤波器作为盲均衡器,两路子滤波器分别以常数模算法准则和判决引导算法准则进行更新,通过加权因子实现两种算法模式自适应切换,完成两种算法的融合处理,加权因子依据归一化均方误差进行调整。为防止信道突发干扰,定义了归一化均方误差信息熵增量,以信息熵增量为判据适时实现均衡器和加权因子重置,使算法在信道突发干扰条件下能实现自适应跟踪。计算机仿真和水池试验处理结果表明:该算法有效地结合了常数模和判决引导算法的优点,具有较好的均衡性能。
Aiming at the difficulty of switching timing between the dual-mode blind equalization algorithm and the constant mode decision-making, a parallel filtering dual-mode fusion blind equalization algorithm is proposed. The algorithm uses a parallel filter as a blind equalizer. The two sub-filters are respectively updated with the rule of constant modulus algorithm and the decision-making guide algorithm. The weighting factor is used to adaptively switch between the two algorithm modes, and the two algorithms are fused and weighted The factors are adjusted according to the normalized mean square error. In order to prevent the channel burst interference, the normalized mean square error information entropy increment is defined, and the equalizer and weighting factors are reset in time according to the increment of information entropy, so that the algorithm can be realized under the condition of channel burst interference Adapt to tracking. The results of computer simulation and pool test show that this algorithm effectively combines the advantages of constant modulus and decision-directed algorithm and has better equilibrium performance.