Power line communication system impulse noise suppression method based on hard threshold tracking

Abstract

The invention discloses an impulse noise suppression method for a power line communication system based on hard threshold tracking, which comprises the following steps of: estimating an NP difficult problem containing an L0 norm of impulse noise into a sparse approximate solution problem by utilizing MM and an iterative solution method on the basis of a compressed sensing theory; then, converting a sparse approximate solution problem into a form containing two-step iteration results, and solving by utilizing an iteration solution method to obtain an estimated value of pulse noise, and finally obtaining an estimated value of a discrete time domain signal without pulse noise interference to finish pulse noise suppression; the method has the advantage that the pulse noise can be accurately estimated.

Description

technical field [0001] The invention relates to a technology for suppressing impulse noise in a power line communication system, in particular to a method for suppressing impulse noise in a power line communication system based on Hard Thresholding Pursuit (HTP). Background technique [0002] Power line communication (Powerline Communication, PLC) is a communication method using power line medium for carrier transmission. As a well-established infrastructure, power line communication can greatly reduce installation time and cost compared to cables and wireless products, and has the ability to penetrate longer-distance structures. Using it for data transmission can greatly reduce communication costs. And based on the ubiquity of power line infrastructure, power line communication has been successfully applied in various application scenarios. The existing typical applications include smart grid, smart transportation, Internet of Vehicles communication, remote meter reading, a...

AI Technical Summary

Problems solved by technology

For example, some researchers proposed an impulse noise subspace tracking (SP) method to estimate and eliminate impulse noise, but the accuracy of this method is not high

Another example: Some researchers proposed to solve L 0 The NP-hard problem of the norm is relaxed into a convex problem, that is, solving the L of the impulsive noise 1 Norm minimization problem, but this method has low accuracy of impulse noise amplitude point estimation

Another example: some researchers proposed a method of Maximum A Posteriori (MAP) criterion to estimate the impulse noise, but since this method needs to know the prior information of the impulse noise, the error is relatively large in the absence of information

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