Adaptive equalization algorithm based on QAM (Quadrature Amplitude Modulation) modulation way

Abstract

The invention discloses an adaptive equalization algorithm based on a QAM (Quadrature Amplitude Modulation) modulation way. The method comprises the following sub-steps that: S1, a data transmitting end transmits a signal including a training sequence; S2, a frame synchronization module determines a frame data starting position and a training sequence position; and S3, a channel estimation module calculates an IIR filter coefficient according to the training sequence, wherein A, when the training sequence calculation is not finished, the IIR filter filters the training sequence signal in order to lower signal correlation, and equalization calculation is performed on the training sequence signal with a large iteration step length according to an LMS (Least Mean Square) equalization algorithm; and B, when the training sequence calculation is finished, the IIR filter filters the signal with a determined coefficient in order to lower the signal correlation, and the equalization calculation is performed on the signal with a small iteration step length according to the LMS equalization algorithm. Thus, an equalizer algorithm has low calculation complexity and a good equalization effect under QAM modulation, and the requirements of actual engineering applications are met.

Description

technical field [0001] The present invention relates to wireless communication baseband signal demodulation technology, especially anti-multipath equalization technology, especially an adaptive equalization algorithm based on QAM modulation mode. Background technique [0002] With the development of modern communication, the data communication business has increased dramatically, and it is necessary to transmit digital information with a larger capacity on a limited frequency band. Quadrature Amplitude Modulation (QAM) is a modulation technology with high frequency band utilization. Both the amplitude and phase of the modulated signal carry data information, so this modulation technology has been widely used. [0003] However, the information symbols transmitted by the communication medium will always produce amplitude, phase distortion and symbol crosstalk due to the non-ideal characteristics of the channel, and at the same time be interfered by additive noise, mainly manif...

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Problems solved by technology

[0004] Since the channel is time-varying, the equalizer usually adopts adaptive technology to track the change of the channel. Among various adaptive algorithms, the existing algorithms have their own advantages and disadvantages. The complexity of the LMS algorithm is low, but its convergence speed is slow; The disadvantage is that the calculation amount is large, and the inverse matrix needs to be calculated; CMA does not need the sending end to send the training sequence, and is not sensitive to the phase of the transmitted signal, but the residual error of the algorithm is relatively large; the MLSE algorithm has the best performance, but the structure is complex and the calculation amount is large, so it is not suitable Applied in high order QAM modulation mode

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