DDPG-Driven Deep-Unfolding With Adaptive Depth for Channel Estimation With Sparse Bayesian Learning
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DOI: 10.1109/tsp.2022.3207269
Abstract: Deep-unfolding neural networks (NNs) have received great attention since they achieve satisfactory performance with relatively low complexity. Typically, these deep-unfolding NNs are restricted to a fixed-depth for all inputs. However, the optimal number of layers… read more here.
Keywords: adaptive depth; channel estimation; channel; deep unfolding ... See more keywords