Semi-Blind Channel Estimation for Dynamic NTN Systems via Spiked Random Matrix Theory
The proposed approach introduces an optimally regularized least-squares formulation that balances training-based information and blind subspace structure and derive a closed-form characterization of the resulting channel mean-squared error and obtain an analytically tractable design of the optimal regularization parame...