Non-Gauss noise-against blind equalization method

Abstract

The invention discloses a non-Gauss noise-against blind equalization method, aiming at providing the non-Gauss noise-against blind equalization method for wireless communication network, in particular between wireless sensor network nodes, in order to guarantee corrective data transmission between wireless sensor nodes. The maximal signal-to-noise energy ratio of an output signal of an equalizer is utilized as a starting point to construct a new cost function. Based on a method for converting the form of constraint condition, an alternative constraint condition is found, the constraint optimization problem is converted into a non-constraint optimization problem, secondary [epsilon]-insensitive loss functions are adopted to construct a solving method conforming to iterative reweighted least squares method, resulting in a global optimal solution for the cost function. The method can lower cell consumption of the wireless sensor network nodes and takes the requirement on small number of data as well as rapid convergence into consideration in the aspect of algorithm design. The algorithm is suitable for the problem of blind equalization for low-order and high-order quadrature amplitude modulation QAM and PSK signals. Drawings attached represent a model for signal transmission between the wireless sensor network nodes according to the invention.

Description

technical field [0001] The invention belongs to the technical field of signal processing of wireless communication, and is suitable for blind equalization against non-Gaussian noise when the channel between nodes of wireless sensor network has multipath fading characteristics. Background technique [0002] As a special kind of wireless network, wireless sensor network especially emphasizes the communication between devices. The wireless sensor network is data-centric, that is, the wireless sensor network nodes are both routers and hosts. The wireless sensor node transmits the locally processed data to the intermediate processing node, and the intermediate processing node acts as a data fusion node, which can perform corresponding fusion and intelligent processing on multiple received information, and finally send the information to the data receiving end (Sink end ). The channel between nodes has typical multipath fading characteristics due to the influence of propagation ...

AI Technical Summary

Problems solved by technology

The purpose of the present invention is to overcome the shortcomings of the traditional blind equalization method based on high-order statistics, such as relying on Gaussian noise assumptions, requiring a large amount of data, and slow convergence speed.

Images