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This article addresses an ML estimation problem by introducing a coherency profile, which means the sizes of the coherent signal groups. We present the Cramer-Rao (CR) bounds for the estimation. An algorithm for implementing it is proposed based on the alternating maximization. Simulation results show that the performance improvement of the estimator over the conventional ML is significant, even with a small number of samples in low SNR.
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Yang-Ho Choi (2000) studied this question.
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