Open AccessConvergence analysis of a joint signal‐to‐noise ratio and channel estimator for frequency selective channels in orthogonal frequency division multiplexing context
Author(s) -
Savaux Vincent,
DjokoKouam Moïse,
Louët Yves,
Skrzypczak Alexandre
Publication year - 2014
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
ISSN - 1751-9683
DOI - 10.1049/iet-spr.2013.0407
Subject(s) - estimator , channel (broadcasting) , algorithm , context (archaeology) , minimum mean square error , signal to noise ratio (imaging) , convergence (economics) , bit error rate , orthogonal frequency division multiplexing , mean squared error , computer science , transmission (telecommunications) , mathematics , preamble , statistics , telecommunications , paleontology , economics , biology , economic growth
In this article, the authors study the convergence of an iterative algorithm for the joint estimation of the signal‐to‐noise ratio (SNR) and the transmission channel in orthogonal frequency division multiplexing context. At each step of the algorithm, the authors use the minimum‐mean‐square error (MMSE)‐based SNR estimation, which feeds the linear MMSE channel estimation. Reciprocally, this efficient channel estimation is used to perform the SNR estimation. The authors provide a proof of convergence of the algorithm to a single value. Furthermore, we derive an accurate approximation of the bias of the estimation. Simulations show that the algorithm converges quickly and verifies the theoretical results. They also show the efficiency of both SNR and channel estimation. By comparing with the existing methods, the authors show that the tradeoff between the number of required pilots in the preamble and the performance of the SNR estimation were improved. Furthermore, for a fixed bit error rate, the SNR gap between the proposed channel estimation and the perfect one is <0.5 dB.