Time-frequency overlapped signal blind separation method based on frequency spectrum symmetry

Abstract

The invention belongs to the technical field of wireless communication, and discloses a time-frequency overlapped signal blind separation method based on frequency spectrum symmetry. The method comprises the following steps: (1) judging whether an effective signal is polluted; (2) finding out sideband information that the effective signal is not polluted; (3) realizing separation in a frequency domain by utilizing sideband properties; (4) performing demodulation. Blind separation of time-frequency overlapped signals is realized by using the sideband characteristic of the signals and adopting afrequency spectrum symmetry method. According to the invention, the sideband property of the modulation signal is fully utilized, half of the frequency spectrum is utilized to recover all transmission information, and the optimal performance of single sideband demodulation is achieved. According to the method, nonlinear transformation is carried out on the received signals by utilizing the cyclicstability characteristic of the time-frequency overlapped signals, so that the signals which are originally aliasing in the time-frequency domain are dispersed, and the transformation domain containsrich information of modulation signals and can be used for modulation identification and parameter estimation.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method for blind separation of time-frequency overlapping signals based on frequency spectrum symmetry and a wireless communication system. Background technique [0002] At present, single-channel blind separation refers to receiving the target signal and one or more interference signals at the same time under the condition of single-antenna reception. The blind signal separation method is used to separate the target signal and the interference signal. The main reason why the time-frequency aliasing signal is difficult to separate is that this is an underdetermined problem, because there is only one received signal, but multiple source signals must be separated. Therefore, it is necessary to fully mine other useful features or prior information of the signal to find new To solve this difficult problem, convert the underdetermined problem into an over...

AI Technical Summary

Problems solved by technology

This calculation needs to estimate the characteristic parameters of the signal first, but the existing technology cannot achieve high parameter estimation accuracy, which in turn affects the separation performance of the signal, and the complexity of the decision feedback system is high, requiring the received data to be long enough

In general, the algorithm has high requirements on signal-to-noise ratio and high complexity

[0003] To sum up, the problems existing in the existing technology are: the existing algorithm has high complexity, poor timeliness, and has high requirements on the signal-to-noise ratio;

In this case, the useful signal cannot be obtained directly

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