Performance comparison between decision-aided maximum likelihood and adaptive decision-aided phase estimation

Abstract

The performance of decision-aided maximum likelihood (DA ML) and adaptive decision-aided (DA) phase estimation algorithms are analytically investigated in different modulation formats. The results show that the DA ML does not suffer from constellation penalty as in the adaptive DA phase estimation, though its performance depends on the memory length. In addition, it is found that the adaptive DA algorithm is more suitable in phase-shift keying formats than in non-constant amplitude systems.