FDD large-scale MIMO channel estimation pilot frequency optimization method based on compressed sensing

A compressed sensing and channel estimation technology, applied in channel estimation, pilot signal allocation, transmission path sub-channel allocation, etc., can solve the problem of limited local scattering of the transmitting antenna, and achieve the effect of improving performance and reducing mean square error

Active Publication Date: 2016-09-28
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0003] A large number of transmitting antenna...

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  • FDD large-scale MIMO channel estimation pilot frequency optimization method based on compressed sensing
  • FDD large-scale MIMO channel estimation pilot frequency optimization method based on compressed sensing
  • FDD large-scale MIMO channel estimation pilot frequency optimization method based on compressed sensing

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[0028] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:

[0029] The present invention includes two main technical problems, one is to transform the channel estimation problem into a compressed sensing problem, thereby modeling the pilot sequence optimization problem as a measurement matrix optimization problem in compressed sensing; the other is to propose a pilot optimization algorithm to solve The measurement matrix is ​​optimized to obtain the optimal pilot matrix. The implementation of these two parts will be introduced below, and the beneficial effect of this pilot allocation method on improving the performance of compressed sensing-based channel estimation will be illustrated through simulation.

[0030] (1) Acquisition of pilot optimization criteria

[0031] Consider a massive MIMO system in FDD mode, the channel is a flat fading channel, the base station has M uniform transmitting antennas space...

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Abstract

The invention discloses an FDD large-scale MIMO channel estimation pilot frequency optimization method based on compressed sensing, and the method comprises the steps: firstly enabling a channel to be modeled into a formula in a large-scale MIMO system: Y=HX+N, wherein H (shown in the description) is a channel matrix, X (shown in the description) is a pilot frequency matrix, Y (shown in the description) is a receiving signal matrix, and N (shown in the description) is channel noise, M is the number of transmitting antennas, and T is the number of pilot frequencies; secondly carrying out the conversion of the channel matrix, and solving the conjugate matrix (shown in the description) of Y, wherein the conjugate matrix (shown in the description) of the channel matrix represents the conversion form of the channel matrix, the conjugate matrix (shown in the description) of the pilot frequency matrix represents the conversion form of the pilot frequency matrix, and the conjugate matrix (shown in the description) of the receiving signal matrix represents the conversion form of the receiving signals of a receiving end; and finally solving an optimal pilot frequency matrix. Because the conjugate matrix (shown in the description) of the channel matrix is a sparse vector, a channel estimation problem can be modeled into a compressed sensing reconstruction problem shown in the description, wherein ||*||<1> represents 1-norm, ||*||<2> represents 2-norm, and epsilon is greater than zero and less than one. The method can guarantee that the FDD MIMO downlink channel estimation based on compressed sensing can remarkably reduce the mean square error of channel estimation, and improves the channel estimation performance.

Description

technical field [0001] The invention relates to the technical field of pilot-aided channel estimation and pilot design in a communication system, in particular to a pilot optimization method for massive MIMO channel estimation based on compressed sensing under FDD. Background technique [0002] In modern wireless communications, the degrees of freedom of massive MIMO systems under FDD (Frequency Division Duplexing) increase, and the diversity and multiplexing gains brought by multiple antennas can significantly improve spectrum efficiency and energy efficiency. In order to obtain the spatial multiplexing gain and the array gain, the base station transmitting end or the user receiving end needs to know channel state information (CSI, channel state information), which needs to be obtained through channel estimation. In the massive MIMO system of TDD mode, the base station can obtain the channel uplink CSI, and the channel reciprocity makes the channel estimation of the downlin...

Claims

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Application Information

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IPC IPC(8): H04L5/00H04L25/02
CPCH04L5/0048H04L25/0204H04L25/0228
Inventor 何雪云胡培利
Owner NANJING UNIV OF POSTS & TELECOMM
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