On the optimal Constant Norm Algorithm, in respect to the EMSE, for blind QAM equalization

A. Goupil, J. Palicot
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Abstract

During the last Eusipco conference [1] we proposed a new class of algorithm, called Constant Norm Algorithm (CNA), which contains the well-known CMA. From this class, two new cost functions well designed for QAM modulation, were derived. The first, named CQA for Constant sQuare Algorithm, is better adapted for QAM than the classical CMA. It results in a lower algorithm's noise without an increase of complexity. This algorithm was derived thanks to the infinite norm which was intuitively better adapted for square mapping modulation than the norm 2 of the CMA. In the same period [4] we proposed a geometrical derivation for computing the Excess Mean Square Error for Bussgang algorithm. Then in respect to this derivation, we prove in this paper that the optimal norm which minimizes the EMSE for QAM modulation is not the infinite norm (even it gives a lower EMSE than the norm 2) but it is the norm 6.
基于EMSE的最优常范数算法用于盲QAM均衡
在上次Eusipco会议上[1],我们提出了一类新的算法,称为恒定范数算法(Constant Norm algorithm, CNA),它包含了众所周知的CMA。在此基础上,导出了两个新的QAM调制成本函数。第一种算法被称为CQA (Constant sQuare Algorithm),它比经典的CMA更适合于QAM。在不增加算法复杂度的前提下,降低了算法的噪声。由于无限范数直观地比CMA的范数2更适合于平方映射调制,因此导出了该算法。在同一时期[4],我们提出了计算Bussgang算法的超额均方误差的几何推导。然后,关于这个推导,我们在本文中证明了最小化QAM调制的EMSE的最佳范数不是无限范数(即使它给出的EMSE低于范数2),但它是范数6。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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