A multi-user detection method and system based on BGIG-SBL

By introducing the Bernoulli Gaussian Inverse Gamma-Sparse Bayesian Learning (BGIG-SBL) method, the parameter update is updated using variational Bayesian inference, which solves the problem of the failure to effectively utilize the sparsity of sparse signals in the existing technology and improves the performance of multi-user detection.

CN116886243BActive Publication Date: 2026-07-24FUZHOU UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
FUZHOU UNIV
Filing Date
2023-07-14
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing multi-user detection algorithms based on sparse Bayesian learning fail to effectively utilize the sparsity of active user indices corresponding to sparse signals on Gaussian inverse gamma prior models, resulting in insufficient detection performance.

Method used

We employ the Bernoulli Gaussian Inverse Gamma-Sparse Bayesian Learning (BGIG-SBL) method, which learns the sparsity of the active user index by introducing binary vectors from the Bernoulli prior model and uses variational Bayesian inference to update parameters to improve the sparsity of the reconstructed signal.

Benefits of technology

It improves the performance of multi-user detection, especially under different signal-to-noise ratio conditions, the BER performance is about 1 dB to 35% better than traditional methods.

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Abstract

The present application relates to a kind of multi-user detection method and system based on BGIG-SBL, the method includes the following steps: step S1, the received signal and equivalent channel matrix of base station are obtained, initialize parameter and hyperparameter, set iteration number initial value and iteration termination condition;Step S2, parameter is updated using variational bayes inference under the prior model based on Bernoulli Gaussian inverse gamma;Step S3, judge whether to meet iteration termination condition, if meet, output reconstruction signal, if not meet, continue to repeat step S2 until meeting iteration termination condition.The method and system are beneficial to improve multi-user detection performance.
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