A signal processing method and device

Abstract

Provided are a method and device for signal processing. The method comprises: acquiring the noise interference energy and the noise interference cross-correlation of each sampling point of a diversity antenna to obtain a second noise interference covariance matrix; performing dimension reduction on the second noise interference covariance matrix to obtain at least one first noise interference covariance matrix; judging whether or not there is a first noise interference covariance matrix abnormality; if there is judged to be a first noise interference covariance matrix abnormality, calculating the ratio of the product of off-diagonal elements to the product of diagonal elements for each first noise interference covariance matrix; respectively decreasing each off-diagonal element of the second noise interference covariance matrix according to one of the ratios and a preset protective margin; and detecting a signal based on the second noise interference covariance matrix with decreased off-diagonal elements. The technical solution of the present invention achieves the aim of anti-interference, reduction of calculation complexity and good robustness.

Description

technical field [0001] The present invention relates to the communication field, in particular to a signal processing method and device. Background technique [0002] In modern mobile communication systems, the number of users is increasing day by day, but frequency resources are limited, so frequency reuse has to be carried out. However, frequency reuse inevitably causes co-frequency and adjacent-frequency interference. In order to ensure the quality of communication, how to suppress interference has gradually become an important issue faced by mobile communications. [0003] At present, the commonly used algorithms that can suppress the influence of interference and noise are: Maximum Ratio Combining (MRC), Interference Rejective Combining (IRC), Spatial Time Interference Rejective Combining (STIRC), continuous interference Cancellation (successive interference cancellation, SIC), parallel interference cancellation (parallel interference cancellation, PIC), etc. Compare...

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Problems solved by technology

However, in some cases, such as the noise-limited situation, the performance of the above-mentioned various interference suppression algorithms is poor, which is caused by the fact that the estimation error of the noise covariance matrix is ​​greater than the performance gain that the above-mentioned algorithms can bring

In another case, due to signal uncertainty and estimation error, the estimated noise covariance matrix will be singular, which will have a fatal impact on the subsequent interference suppression algorithm, resulting in receiver error

[0005] A method of modifying the covariance matrix and performing subsequent signal detection in the prior art, the judgment of the singularity of the matrix and the calculation of the correction amount are based on the entire received signal, rather than directly obtained from the covariance matrix. The correction process However, it is aimed at the covariance matrix, so there are problems that the judgment of whether the matrix is ​​singular may not be accurate, and the loading may not be optimal. In addition, it is more complicated to implement

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