The Ricean K-factor is a practical channel quality measure in many wireless communication applications as it exhibits a fast estimation convergence compared with the explicit estimation of performance metrics such as error rates. Recently, it has been shown that estimation of the K-factor can be improved relative to envelope-based detectors through the use of complex (I/Q) channel observations. In this paper, an analysis of the maximum likelihood estimator of the K-factor from I/Q samples is presented, which illustrates the bias of previous estimators. An improved estimator is then proposed, which has superior bias and efficiency for short data records. For mobile applications, a reliable estimator of the Doppler shift of the specular component is incorporated. Simulation results for a range of channel conditions illustrate that the proposed estimator outperforms prior techniques, and provide insight into the record lengths required to achieve a desired estimation accuracy.
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Baddour et al. (2008) studied this question.
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