Low-complexity 5G NR channel estimation method based on compressed sensing

A technology of compressed sensing and channel estimation, which is applied in the field of low-complexity 5G NR channel estimation, can solve the problems of low complexity of the least squares method, increase of algorithm complexity, and poor performance of channel estimation, so as to solve the problem of large pilot overhead and reduce complexity degrees, avoiding the effect of solving

Inactive Publication Date: 2020-06-05
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

The complexity of the least square method is low, but the influence of noise is not considered, and the performance of channel estimation is poor; the minimum mean square error considers noise, but there is a solution to the correlation matrix and inverse matrix, which increases the complexity of the algorithm
Moreover, these methods require a large amount of pilot information, and there is a phenomenon of waste of frequency band resources for pilots that do not carry useful information.

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  • Low-complexity 5G NR channel estimation method based on compressed sensing
  • Low-complexity 5G NR channel estimation method based on compressed sensing
  • Low-complexity 5G NR channel estimation method based on compressed sensing

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[0048] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0049] see Figure 1 ~ Figure 2 , figure 1 It is a flow chart of a low-complexity 5G NR channel estimation method based on compressed sensing of the present...

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Abstract

The invention relates to a low-complexity 5G NR channel estimation method based on compressed sensing, and belongs to the field of wireless communication. The method comprises the following steps: solving a channel time domain information pair by using a compressed sensing theory, and performing Fourier transform to obtain corresponding frequency domain information to calculate a channel frequencydomain autocorrelation matrix RHH; quickly estimating a signal-to-noise ratio SNR by using the extracted pilot signal; according to the characteristics of a cyclic matrix, solving an LMMSE estimationmatrix, introducing a Toeplitz matrix, and calculating a pilot frequency LMMSE channel estimation value based on compressed sensing. The method starts from traditional LMMSE channel estimation, the characteristics of the compressed sensing theory and the cyclic matrix are combined, the frequency band utilization rate is increased, and meanwhile the complexity is reduced.

Description

technical field [0001] The invention belongs to the field of wireless communication, and relates to a low-complexity 5G NR channel estimation method based on compressed sensing. Background technique [0002] In the field of wireless communication, with the development of 5G communication, channel estimation, as an important part of 5G NR, realizes the function of demodulating the information of the sending end by obtaining detailed information of the channel, and its accuracy directly affects the performance of the entire system. Traditional channel estimation methods include the least square method and the least mean square error method. The complexity of the least square method is low, but the influence of noise is not considered, and the performance of channel estimation is poor; the minimum mean square error considers noise, but there is a solution to the correlation matrix and the inverse matrix, which increases the complexity of the algorithm. Moreover, these methods ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L25/02H04L27/26
CPCH04L25/0224H04L25/0242H04L27/2695
Inventor 邓炳光闵小芳张治中叶倩倩纪汪勇江航
Owner CHONGQING UNIV OF POSTS & TELECOMM
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