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A Low Training Overhead Channel Estimation Method for Hybrid Large-Scale MIMO-OFDM Systems

A MIMO-OFDM and channel estimation technology, applied in the field of hybrid massive MIMO-OFDM system channel estimation, can solve the problems of noise-free signal tensor not having low-rank characteristics, high training overhead, etc., so as to reduce training overhead and estimation effect of error

Active Publication Date: 2022-06-21
SOUTHEAST UNIV
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Problems solved by technology

However, in this scheme, the noise-free signal tensor received by the hybrid massive MIMO-OFDM system does not have low-rank characteristics, and the training overhead is still large

Method used

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  • A Low Training Overhead Channel Estimation Method for Hybrid Large-Scale MIMO-OFDM Systems
  • A Low Training Overhead Channel Estimation Method for Hybrid Large-Scale MIMO-OFDM Systems
  • A Low Training Overhead Channel Estimation Method for Hybrid Large-Scale MIMO-OFDM Systems

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Embodiment Construction

[0054] The technical solutions of the present invention will be further introduced below with reference to the accompanying drawings and specific embodiments.

[0055] The low training overhead hybrid massive MIMO-OFDM system channel estimation method of the present invention, such as figure 2 shown, the hybrid massive MIMO-OFDM system includes a Q a The base station with the root antenna and K randomly distributed single-antenna users; the hybrid massive MIMO-OFDM system has a total of N subcarriers, which are multiplexed by all users; the base station antenna adopts a uniform linear array, and the antenna spacing is equal to half wavelength; the base station adopts a hybrid structure , with Q r a RF links combine the received signal into the RF band, each with a high-resolution ADC to stream the data to the baseband processor;

[0056] like figure 1 The specific method is:

[0057] S1. Establish a hybrid massive MIMO-OFDM system channel model, uplink signal transmission...

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Abstract

The invention discloses a mixed large-scale MIMO-OFDM system channel estimation method with low training overhead, which is suitable for use in the communication field. First establish a hybrid large-scale MIMO-OFDM system channel model, uplink signal transmission model, and hybrid structure sampling model, so that the base station can obtain an incomplete baseband signal sampling tensor for channel estimation; the incomplete baseband signal sampling tensor Perform modulo 3 expansion to obtain the incomplete baseband signal sampling matrix; the base station designs a matrix completion algorithm that takes the incomplete baseband signal sampling matrix as input and outputs a complete estimated matrix; performs modulo 3 expanded inverse operation on the complete estimated matrix, The estimated tensor is obtained, and then the channel estimation is completed according to the estimated tensor and the known pilot matrix. This method can significantly reduce the training overhead, and can reduce the estimation error by increasing the number of subcarriers.

Description

technical field [0001] The invention relates to a channel estimation method for a hybrid massive MIMO-OFDM system, and is particularly suitable for a low training overhead hybrid massive MIMO-OFDM system channel estimation method used in the field of wireless communication technology. Background technique [0002] Massive Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system has become a promising wireless technology due to its high spectral and energy efficiency. In a massive MIMO-OFDM system with an all-digital architecture, each antenna is equipped with a Radio Frequency (RF) chain with a high-resolution Analog to Digital Converter (ADC), thus increasing the cost. To reduce cost, hybrid analog / digital architectures with RF chains and ADC counts are widely used. [0003] In order to realize a hybrid massive MIMO-OFDM system, it is crucial to obtain accurate Channel State Information (CSI). Due to the reduced number of RF chains, the...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L25/02H04L27/26
CPCH04L25/0204H04L25/0224H04L25/0244H04L27/2601
Inventor 朱鹏程徐军盛政李佳珉尤肖虎
Owner SOUTHEAST UNIV
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