Impulse noise elimination method and device

Abstract

The invention provides an impulse noise eliminating method and device. The method comprises that S1) T transmitting antennas of an antenna system transmit frame headers and frame bodies of signal frames; S2) each reception antenna obtains the value of a reserved subcarrier in the frequency domain of the frame body to form the frequency-domain observation vector of impulse noise signals, and according to a multidimensional impulse noise combined sampling matrix composed of R frequency-domain observation vectors, a structural compressive sensing model is obtained; S3) estimation of time-domain impulse noise signals corresponding to the R reception antennas is obtained by utilizing the structural compressive sensing algorithm; and S4) the estimation of the time-domain impulse noise signals is subtracted from the corresponding time domain signals of the frame bodies of the R reception antennas to obtain frame body data of the signal frames of the R reception antennas of which impulse noise signals are eliminated. Thus, MIMO-OFDM impulse noises can be accurately estimated, and the spectral efficiency and robustness of the system are effectively improved.

Description

technical field [0001] The invention relates to the technical field of digital signal transmission, in particular to a method and device for eliminating impulse noise based on spatial correlation and structured compressed sensing. Background technique [0002] In broadband high-speed data transmission, there are complex noise interferences such as frequency selective fading, time selective fading, narrowband interference, and impulse noise (Impulse Noise, IN), which affect the quality of data transmission. In order to overcome the aforementioned harsh channel conditions, Orthogonal Frequency Division Multiplexing (OFDM) technology has been widely used. OFDM technology mainly includes Time Domain Synchronous Orthogonal Frequency Division Multiplexing (Time Domain Synchronous OFDM, TDS-OFDM), Cyclic-Prefix OFDM (CP-OFDM) and Zero-Padding OFDM (Zero-Padding OFDM). , ZP-OFDM) and other categories. Because OFDM has the excellent characteristics of overcoming frequency selectivi...

AI Technical Summary

Problems solved by technology

[0005] The existing foreign traditional impulse noise estimation method based on compressed sensing uses frequency-domain dedicated empty subcarriers to form an observation sequence for estimation, but it has certain defects: on the one hand, according to the theory of compressed sensing, the existence of background noise has a significant impact on the algorithm effect , in the case of strong additive white Gaussian noise (AWGN), this method has to occupy a large number of dedicated empty subcarriers as the observation sequence, otherwise it cannot accurately estimate the low Interference-to-Noise Ratio (INR) The impulse noise signal will lead to a serious loss of spectral efficiency

However, the number of reserved subcarriers in the existing power line communication standards and wireless broadcasting standards is very limited. In many application scenarios, the interference-to-noise ratio of impulse noise is not high compared with Gaussian noise. Not only the performance of this method will be seriously affected; another On the one hand, the compressive sensing algorithm of this method starts iterative calculation from the initial state, the number of iterations is large, and the computational complexity needs to be reduced urgently

Furthermore, there is currently no research or technology for structured multi-dimensional joint impulse noise estimation for the spatial correlation of impulse noise in MIMO systems, that is, the characteristic of the same time-domain position of impulse noise signals on multiple receiving antennas

[0006] In summary, traditional anti-impulse noise methods and existing compressed sensing-based impulse noise estimation methods suffer from serious loss of spectral efficiency, low performance, and high computational complexity.

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