Electrical Engineering and Systems Science > Signal Processing
[Submitted on 4 Feb 2021]
Title:Separable Joint Blind Deconvolution and Demixing
View PDFAbstract:Blind deconvolution and demixing is the problem of reconstructing convolved signals and kernels from the sum of their convolutions. This problem arises in many applications, such as blind MIMO. This work presents a separable approach to blind deconvolution and demixing via convex optimization. Unlike previous works, our formulation allows separation into smaller optimization problems, which significantly improves complexity. We develop recovery guarantees, which comply with those of the original non-separable problem, and demonstrate the method performance under several normalization constraints.
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