On Models, Bounds, and Estimation Algorithms for Time-Varying Phase Noise
Paper in proceedings, 2011
In this paper, first, a new discrete-time model of phase noise for digital communication systems, which is a more accurate model compared to the classical Wiener model, is proposed based on a comprehensive continuous-time representation of time-varying phase noise, and statistical characteristics of this model are derived. Next, the non-data-aided (NDA) and decision-directed (DD) maximum-likelihood (ML) estimators of time-varying phase noise, using the proposed discrete-time model are derived. To evaluate the performance of the proposed estimators, the Cramer-Rao lower bound (CRLB) for each estimation approach is derived and by using Monte-Carlo simulations it is shown that the mean-square error (MSE) of the proposed estimators converges to the CRLB at moderate signal-to-noise ratios (SNR). Finally, simulation results show that the proposed estimators outperform existing estimation methods as the variance of the phase noise process increases.
non-data-aided (NDA)
Wiener model
Time-varying phase noise
decision-directed (DD)
maximum-likelihood (ML)
Cramer-Rao lower bound (CRLB)
phase noise estimation
Author
M Reza Khanzadi
Chalmers, Microtechnology and Nanoscience (MC2), Microwave Electronics
GigaHertz Centre
Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems
Hani Mehrpouyan
Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems
Erik Alpman
Semcon
Tommy Svensson
Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems
Dan Kuylenstierna
Chalmers, Microtechnology and Nanoscience (MC2), Microwave Electronics
GigaHertz Centre
Thomas Eriksson
Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems
GigaHertz Centre
Chalmers, Signals and Systems, Information theory
5th International Conference on Signal Processing and Communication Systems (ICSPCS2011)
Art Nr. 6140897- 6140897
Areas of Advance
Information and Communication Technology
Subject Categories
Telecommunications
Signal Processing
DOI
10.1109/ICSPCS.2011.6140897
ISBN
978-145771180-0