A deep learning-inspired compressed sensing framework for sparse channel estimation in optical wireless communications
Simulations show that the proposed DL-CS method offers a practical training-free enhancement of classical greedy algorithms for sparse channel estimation in optical wireless communications, and improves NMSE and BER over OMP and CoSaMP, with runtime close to that of OMP.