Code-aided SNR estimation based on expectation maximisation algorithm

摘要

A code-aided signal-to-noise ratio (SNR) estimator based on the expectation maximisation algorithm is proposed. The method itera-tively uses the soft information from the channel decoder and significantly improves estimation precision in the low SNR regime. It can be extended to higher-order modulation such as MPSK and MQAM directly. Introduction: Signal-to-noise ratio (SNR) estimation is an important problem in power control, turbo decoding, link adaptation, etc. Many papers have been published on SNR estimation over the AWGN channel. In, a variety of data-aided (DA) and non-data-aided (NDA) SNR estimators are compared. In, a hybrid DA/NDA estimator jointly using pilots and data symbols is proposed to improve estimation accuracy.