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http://hdl.handle.net/10397/38057
Title: | MMSE recursive estimation of high phase-noise that is Wiener non-stationary | Authors: | Su, YT Wong, KT Ho, RKP |
Keywords: | Least mean squares methods Phase noise Recursive estimation Signal detection Stochastic processes |
Issue Date: | 2009 | Source: | IEEE Radar Conference, 2009 : RadarCon 09 ; 4 - 8 May 2009, Pasadena, CA, USA, p. 1-5 (CD) How to cite? | Abstract: | To estimate Wiener phase noise of arbitrarily large magnitude (relative to the symbol duration), this work pioneers a linear minimum-mean-square error (LMMSE) discrete-time estimator. This proposed estimator may be pre-set to any arbitrary number of taps and any arbitrary latency. The coefficients of this linear estimator depend only on the values of the signalto-(additive)-noise ratio and the phase-noise variance. Moreover, rigorous analysis here (1) proves that this sequence of LMMSE-weights are unimodal when plotted against the weight-index, (2) derives an upper bound and a lower bound, in closed forms, for the LMMSE-weights, and (3) proves that this sequence of LMMSE-weights converges to be Laplacian when plotted against the weight-index, as the number of taps approaches infinity. | URI: | http://hdl.handle.net/10397/38057 | ISBN: | 978-1-4244-2870-0 978-1-4244-2871-7 (E-ISBN) |
DOI: | 10.1109/RADAR.2009.4976966 |
Appears in Collections: | Conference Paper |
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