Impulse Noise Suppression Method for Sparse Iterative Covariance Estimation in Power Lines

Abstract

The invention discloses a pulse noise suppression method for sparse iterative covariance estimation in power lines. At the sending end, the discrete time-domain signal with a cyclic prefix is ​​transmitted to the receiving end through a channel; at the receiving end, the received signal is first projected On the empty subcarrier matrix, a mixed signal containing only impulse noise and Gaussian noise is obtained; using sparse iterative covariance estimation, the power of the mixed signal is obtained, and then the power of the impulse noise is obtained; the estimated value of the impulse noise is obtained by using the linear mean square error ; Subtract the estimated value of impulse noise from the received signal to complete the suppression of impulse noise; the advantage is that the sparse iterative covariance estimation adopted has a higher resolution, and can estimate the power of the mixed signal more accurately, so that The estimated impulse noise is more accurate, so that the suppression effect of impulse noise is better.

Description

technical field [0001] The invention relates to an impulse noise suppression technology, in particular to an impulse noise suppression method for sparse iterative covariance estimation in power lines. Background technique [0002] With the rapid development of the smart grid, the use of power line communication (PowerLine Communication, PLC) has gradually attracted people's attention. Power line communication is a communication method that uses power line media for data transmission. In the power line communication system, the channel characteristics are complex and the multipath effect is obvious. In order to combat the multipath effect, multi-carrier Orthogonal Frequency Division Multiplexing (OFDM) technology is generally used. The early design of power line communication only considered the transmission of electricity, and did not consider the transmission of data signals. In reality, communication has relatively high requirements for equipment, but the existing power ...

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Problems solved by technology

However, these methods are more suitable for Bernoulli Gaussian impulse noise. Through simulation experiments, it is found that for the impulse noise generated by the Middleton type A model that is closer to the actual situation, the impulsive noise estimation performance of these methods is poor, resulting in the inability to effectively suppress the impulsive noise.

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