VIGAMP-based impulse noise estimation in power line communication

Power line communication (PLC) is essential for smart grid applications but struggles with noise due to its use of electrical lines for data transmission. PLC systems are particularly affected by bursty impulse noise. In order to estimate the impulse noise, this paper proposes a variational inference generalized approximate message passing (VIGAMP) based algorithm that simplifies complexity and improves performance for PLC-OFDM system. Compared to existing Sparse Bayesian Learning algorithms, Simulations reveal that the proposed method offers better Bit Error Rates performance and faster convergence.