A Joint Estimation Algorithm for Dual-Mode Channel Fading and Power Line Impulse Noise in Low-Voltage Station Areas

Channel fading and impulse noise in low-voltage station areas severely hinder data acquisition, and effective estimation of dual-mode channel data and state is the critical prerequisite for adaptive transmission. To address the impact of impulse noise on the performance of Orthogonal Frequency Division Multiplexing (OFDM) power line communication systems, this paper proposes a wireless-assisted joint estimation algorithm of channel fading and impulse noise in dual-mode OFDM systems. Firstly, a model of the dual-mode OFDM system combining power line and wireless links is established, and the initial channel estimation is obtained based on Linear Minimum Mean Square Error (LMMSE), the wireless link is used as an aid to provide a relatively reliable initial symbol estimation for the power line link. Then, a two-stage approach for initial impulse noise estimation is proposed: firstly, the possible impulse noise is located based on constructed residuals to form a support set, followed by refinement of the impulse amplitude using Single Measurement Vector Sparse Bayesian Learning (SMV-SBL). Finally, a decision-feedback iterative update is performed to iteratively optimize the symbol detection, channel estimation, and impulse noise estimation processes. Combined with adaptive dual-mode fusion, this approach improves estimation accuracy. Simulation results demonstrate that the proposed algorithm achieves significant improvements in estimation accuracy and bit error rate.