TY - GEN
T1 - Smoothing PLLs for QAM dynamical phase estimation
AU - Yang, J.
AU - Geller, B.
AU - Herzet, C.
AU - Brossier, J. M.
PY - 2009/11/19
Y1 - 2009/11/19
N2 - This paper presents a near-optimum, low-complexity, fixed-interval smoothing algorithm that approaches the performance of an optimal smoother for the price of two low-complexity sequential estimators (two PLLs). The proposed Smoothing PLL (S-PLL) algorithm is easy to implement and fits the Cramer-Rao bounds over a wide range of signal-to-noise ratios. Moreover we show that, compared to the conventional forward loop, the proposed scheme allows to have a large gain of several dBs and is able to track frequency offsets.
AB - This paper presents a near-optimum, low-complexity, fixed-interval smoothing algorithm that approaches the performance of an optimal smoother for the price of two low-complexity sequential estimators (two PLLs). The proposed Smoothing PLL (S-PLL) algorithm is easy to implement and fits the Cramer-Rao bounds over a wide range of signal-to-noise ratios. Moreover we show that, compared to the conventional forward loop, the proposed scheme allows to have a large gain of several dBs and is able to track frequency offsets.
KW - Dynamical phase estimation
KW - Phase-locked loop (PLL)
KW - QAM
KW - Smoothing algorithm
UR - https://www.scopus.com/pages/publications/70449476253
U2 - 10.1109/ICC.2009.5199465
DO - 10.1109/ICC.2009.5199465
M3 - Conference contribution
AN - SCOPUS:70449476253
SN - 9781424434350
T3 - IEEE International Conference on Communications
BT - Proceedings - 2009 IEEE International Conference on Communications, ICC 2009
T2 - 2009 IEEE International Conference on Communications, ICC 2009
Y2 - 14 June 2009 through 18 June 2009
ER -