IRS-based large-scale MIMO cascade channel estimation method under hybrid low-precision architecture

Abstract

The invention discloses an IRS-based large-scale MIMO cascaded channel estimation scheme under a hybrid low-precision architecture, which comprises the following steps: firstly, a base station end performing uniform division and phase configuration of units on a large-scale reflective array plane by sending a downlink configuration information signaling, and selecting a central unit of each sub-array plane to perform channel estimation; secondly, designing an isotropic analog receiver which adopts a full-connection phase shifter network, and enabling phases of all phase shifters to be uniformly distributed; then, the base station obtaining sparse information of an angle domain millimeter wave channel by utilizing a compressed sensing technology, so that a digital estimator is optimally designed, and angle domain channel estimation is obtained; and finally, through sparse recovery and angle domain inverse transformation, obtaining the cascade channel estimation of the sub-array surface,and further deducing to obtain the cascade channel estimation of all the IRS array surfaces. According to the method, the performance of channel estimation can be remarkably improved, and the amplification effect of the IRS on quantization noise is effectively inhibited.

Description

technical field [0001] The present invention relates to a channel estimation method in the communication field, and more specifically relates to a cascaded channel estimation method based on IRS-based massive MIMO under a mixed low-precision architecture. Background technique [0002] In recent years, communication technology has made a breakthrough and gradually matured, and the mobile communication industry has developed rapidly worldwide. Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) is a key technology for fifth-generation (5G) wireless systems, promising to improve the spectral efficiency of wireless communications by an order of magnitude. Potential applications and examples of practical mmWave massive MIMO have also been demonstrated in the 3rd Generation Partnership Project (3GPP) New Radio standard. However, massive MIMO is characterized by large antenna arrays and requires a large number of radio frequency (RF) chains, which are expensive ...

AI Technical Summary

Problems solved by technology

Secondly, since most of the IRS is passive and cannot send and receive pilot signals, it is impossible to estimate the independent channels at both ends like in conventional MIMO networks, and can only estimate the cascaded channels

Therefore, the channel estimation problem is more challenging when considering the application of IRS in low-precision hybrid massive MIMO

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