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This chapter presents a blind demixing model for joint data decoding and channel estimation in IoT networks, without transmitting pilot sequences. The problem formulation based on the cyclic convolution in the time domain is first introduced, which is then reformulated in the Fourier domain for the ease of algorithm design. A convex relaxation approach based on nuclear norm minimization is first presented as a basic solution. Next, several nonconvex approaches are introduced, including both regularized and regularization-free Wirtinger flow and the Riemannian optimization algorithm. The mathematical tools for analyzing nonconvex approaches are also provided.
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