Beamforming method based on landweber iterative method

Abstract

The invention discloses a beam forming method based on a Landweber iteration method. The beam forming method comprises the following steps: demodulating a band-pass communication signal to a baseband through a base station antenna, and then carrying out discrete sampling; solving a corresponding covariance matrix by using front N discrete sampling data as a training sequence, calculating a relaxing factor alpha in a Landweber iteration formula and solving a corresponding beam forming weight w(m) through the Landweber iteration formula; substituting the obtained weight w(m) to a cost function G(m) and solving an ideal iteration stop number based on the Landweber iteration method in the cost function G(m), namely solving a regularization factor m for enabling the cost function G(m) to be minimum and the corresponding an optimal weight of the Landweber iteration method; finally carrying out beam forming operation on the subsequent sampling sequence by using the weight of the solved Landweber iteration method. According to the beam forming method, the beam forming weight is solved by using Landweber iteration, the iteration number is determined by simplifying the cost function, and finally an iteration solution capable of resisting system errors is obtained.

Description

technical field [0001] The invention belongs to the field of communication signal processing, and more specifically relates to a beam forming method for receiving signals in a smart antenna. Background technique [0002] As one of the key technologies in the third-generation and later mobile communications, smart antenna technology can improve the signal-to-interference-noise ratio, improve communication quality, increase system capacity, increase the number of users, increase frequency utilization, and reduce electromagnetic interference, etc. Many advantages. The beam forming method is the core of the smart antenna, and its quality directly determines the performance of the smart antenna. Conventional beamforming methods include Sampling Matrix Inversion (SMI) method, Diagonal Loading (DL) method and Eigensubspace Projection (ESB) method. Among them, the SMI method is simple to calculate and does not need to determine the size of the empirical factor in advance. However...

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Problems solved by technology

However, this method is particularly sensitive to systematic errors, and a very small error will lead to a significant decrease in the performance of the method, which is difficult to apply in practice

The DL method is an improvement to the SMI method, but this method needs to determine the size of a noise-related loading factor in advance. At present, there is no effective method to calculate the size of the factor. Generally, empirical values ​​are used.

When the signal-to-noise ratio is large, the ESB method can show good robustness, but when the signal-to-noise ratio is small, the performance of this method will drop sharply

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