摘要
该文提出一类新的Bussgang指数拓展多模算法,进一步降低传统Bussgang类盲均衡算法收敛时的稳态误差的效果。分析了新代价函数和误差函数等对算法性能的影响,并给出了算法复杂度分析,展示了如何利用作图法求得星座特征常数R的过程。为了削弱该算法对于高阶统计量信息的依赖,提出一种星座特征常量R的近似计算方法,使得星座特征常数不再成为新算法良好工作所必须的先验知识。最后以星座点甚密集方形QAM和非方形QAM系统为例,通过仿真验证该算法对密集QAM系统的盲均衡能力。
A novel Bussgang category of blind equalization with Exponential Expanded Multi-Modulus Algorithm （EEMMA） is proposed. Comparing with those traditional Bussgang blind equalization algorithms, the proposed one can decrease further the steady-state error. This paper analyses the new cost function, and error function effects on the performance of the algorithm, and analyses the complexity of the novel algorithm. Meantime, a calculation approach of constellation characteristic constant R using graphing method is presented. An approximate calculation method of constellation characteristic constant R is shown to reduce the dependence on the information of high order statistics. The approximate calculation method of R makes the proposed algorithm does not rely on any priori knowledge of constellations. Finally, using dense square and non-square QAM systems, simulation results demonstrate the effectiveness of this new algorithm.
出处
《电子与信息学报》
EI
CSCD
北大核心
2013年第9期2187-2193,共7页
Journal of Electronics & Information Technology
基金
国家自然科学基金青年项目(61201426)资助课题
关键词
无线通信
信号处理
盲均衡
Bussgang算法
星座特征常数
Wireless communication
Signal processing
Blind equalization
Bussgang algorithm
Constellationcharacteristic constant
