Tensor-Based Channel Estimation for Dual-Polarized Massive MIMO Systems
Tensor-Based Channel Estimation for Dual-Polarized Massive MIMO Systems is a scholarly work, published in 2018 in ''IEEE Transactions on Signal Processing''. The main subjects of the publication include mathematics, computer science, 5G, telecommunications, MIMO, tensor, mathematical optimization, algorithm, channel, tensor decomposition, power control, dual, and control theory. The authors first reveal that the DD channel with DP arrays at\nthe transmitter and receiver can be naturally modeled as a low-rank tensor, and\nthus the key parameters of the channel can be effectively estimated via tensor\ndecomposition algorithms.\n On the theory side, authors show that the DD-DP parameters are identifiable under\nvery mild conditions, by leveraging identifiability of low-rank tensors.\nFurthermore, a compressed tensor decomposition algorithm is developed for\nalleviating the downlink training overhead.