Long code DS-CDMA signal blind separation method based on tensor low-rank decomposition

Abstract

The invention belongs to the blind despreading technical field, and especially relates to a synchronous long code DS-CDMA signal blind separation method based on deletion tensor low-rank decomposition. The invention provides a synchronous long code DS-CDMA signal blind separation method suitable for the case in which a spread spectrum sequence period is non-integer times of a spreading factor. The method comprise: converting a blind separation problem of synchronous long code DS-CDMA signals intercepted through multiple channels into a low-rank decomposition problem of a synchronous long code DS-CDMA signal deletion tensor model; realizing the low-rank decomposition of the deletion tensor model through an interpolation ALS algorithm; and finally obtaining the information code matrix of multiple users and completing signal blind separation. The method possesses better performance even under the condition of a low SNR (Signal Noise Rate) or short data.

Description

technical field [0001] The invention belongs to the technical field of blind despreading, and in particular relates to a method for blindly separating synchronous long code DS-CDMA signals based on missing tensor low-rank decomposition. Background technique [0002] Direct Sequence Spread Spectrum (DSSS) communication technology is one of the most commonly used technologies in modern communication technology. Because this technology can effectively improve the anti-jamming and anti-interception capabilities of wireless communication, it has important practical value and research significance in civilian and military fields. The DSSS communication technology multiplies the information code and a high-speed spread spectrum sequence at the sending end to achieve the effect of expanding the signal spectrum and reducing the signal spectral density. [0003] According to the relationship between the spread spectrum sequence period and the spread factor, DSSS communication technol...

AI Technical Summary

Problems solved by technology

For these methods, longer signal samples are usually required to improve the estimation accuracy, and in some practical situations, non-cooperative receivers cannot obtain longer signal samples, so these blind separation methods based on statistics cannot obtain ideal Effect

In addition, in order to suppress the interference between multiple users, the traditional multi-user blind separation method has certain requirements on the spreading code and information code of each user. For example, the spreading sequence of each user must have good orthogonality, the information code The sequences are uncorrelated or have characteristics such as constant modulus and finite sets, etc., and these requirements are often not met in engineering applications

In the method of multi-channel reception, many traditional blind separation algorithms based on multi-channel need to use the direction finding algorithm to estimate the direction of arrival of the signal, and then realize the blind separation through spatial filtering. In the case of a low signal-to-noise ratio, the estimation accuracy of the direction finding algorithm is difficult to guarantee, and the amplitude and phase consistency between channels are also difficult to meet the requirements, so the effect of these methods is not ideal

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