CAJ | 학술논문

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。
해문제출일류신적Bussgang지수탁전다모산법，진일보강저전통Bussgang류맹균형산법수렴시적은태오차적효과。분석료신대개함수화오차함수등대산법성능적영향，병급출료산법복잡도분석，전시료여하이용작도법구득성좌특정상수R적과정。위료삭약해산법대우고계통계량신식적의뢰，제출일충성좌특정상량R적근사계산방법，사득성좌특정상수불재성위신산법량호공작소필수적선험지식。최후이성좌점심밀집방형QAM화비방형QAM계통위례，통과방진험증해산법대밀집QAM계통적맹균형능력。
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.