ML-based blind symbol rate detection for multi-rate receivers

This contribution deals with symbol rate detection algorithms for multi-rate receivers. From the maximum likelihood criterion, we derive two blind rate detection algorithms: the first follows from a low SNR approximation of the likelihood function, while the second makes use of the expectation-maximization (EM) algorithm. We compare the proposed detectors with a cyclic correlation-based scheme from literature in terms of their rate detection error probability. The proposed ML-based algorithms turn out to substantially outperform the correlation-based algorithm.