摘要
为了提高高阶QAM信号的盲均衡性能,本文提出了一种新的多模混合盲均衡算法。该算法首先对加权多模盲均衡算法进行改进,提出了新的加权因子选取方法;然后将其与判决引导算法有机结合,构造出新的多模混合盲均衡代价函数对均衡器系数自适应更新。与其他盲均衡算法相比,该算法不仅降低了均衡后的稳态误差,增强了对不同调制阶数的适应能力,而且大幅度提高了均衡器的收敛速度。仿真结果验证了该算法的有效性。
For improving the equalization performance of high-order QAM signals,a new multi-modulus based hybrid blind equalization algorithm is proposed.The algorithm uses a new weight factor definition method to improve the weighted multi-modulus blind equalization algorithm（WMMA） and combines it with the decision directed algorithm to construct a new multi-modulus hybrid blind equalization cost function for updating the equalizer coefficients.Compared with other blind equalization algorithms,the new algorithm reduces the residual error and improves the adaptive capacity to different modulation orders.Furthermore,the convergence rate increases.Simulation results prove the feasibility of the new algorithm.
出处
《数据采集与处理》
CSCD
北大核心
2011年第1期8-14,共7页
Journal of Data Acquisition and Processing
基金
河南省基础与前沿研究基金(082300413205)资助项目
关键词
盲均衡
高阶QAM
多模算法
混合盲均衡算法
blind equalization
high-order QAM
multi-modulus algorithm
hybrid blind equalization algorithm
