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On Models, Bounds, And Estimation Algorithms For Time-Varying Phase Noise, M. Reza Khanzadi, Hani Mehrpouyan, Erik Alpman, Tommy Svensson, Dan Kuylenstierna, Thomas Eriksson
On Models, Bounds, And Estimation Algorithms For Time-Varying Phase Noise, M. Reza Khanzadi, Hani Mehrpouyan, Erik Alpman, Tommy Svensson, Dan Kuylenstierna, Thomas Eriksson
Hani Mehrpouyan
In this paper, a new discrete-time model of phase noise for digital communication systems, based on a comprehensive continuous-time representation of time-varying phase noise is derived and its statistical characteristics are presented. The proposed phase noise model is shown to be more accurate than the classical Wiener model. Next, using the proposed discrete-time model, the non-data-aided (NDA) and decision-directed (DD) maximum-likelihood (ML) estimators of time-varying phase noise are derived. To evaluate the performance of the proposed estimators, the Cramér-Rao lower bound (CRLB) for each estimation approach is derived and by using Monte-Carlo simulations it is shown that the mean-square error …
Optimal And Approximate Methods For Detection Of Uncoded Data With Carrier Phase Noise, Rajet Krishnan, Hani Mehrpouyan, Thomas Eriksson, Tommy Svensson
Optimal And Approximate Methods For Detection Of Uncoded Data With Carrier Phase Noise, Rajet Krishnan, Hani Mehrpouyan, Thomas Eriksson, Tommy Svensson
Hani Mehrpouyan
Previous results in the literature have shown that derivation of the optimum maximum-likelihood (ML) receiver for symbol-by-symbol (SBS) detection of an uncoded data sequence in the presence of random phase noise is an intractable problem, since it involves the computation of the conditional probability distribution function (PDF) of the phase noise process. In this paper, we seek to minimize symbol error probability (SEP), which is achieved by SBS detection of the sequence based on all received signals. We show that the ML detector for this problem can be formulated as a weighted sum of central moments of the conditional PDF …