Gaussian message transfer iterative detection method for MU-MIMO (Multiuser Multiple-Input Multiple-Output) system

Abstract

The invention relates to a Gaussian message transfer iterative detection method for an MU-MIMO (Multiuser Multiple-Input Multiple-Output) system. Implementation of the method comprises the steps of (1) receiving an information sequence; (2) performing initialization; (3) updating a sum node message; (4) updating a variable node message; (5) judging whether the maximum number of iterations reaches or not; and (6) determining the variance and a signal value of the variable node. The Gaussian message transfer iterative detection method is applicable to a multiuser multiple-input multiple-out (MU-MIMO) system with the number of users and the number of antennas being great and the number of users being less than the number of antennas. According to the invention, a relaxation parameter is introduced to perform scaling on a receiving sequence and a channel state matrix, an item is added to a mean update formula of the variable node so as to minimize the spectral radius of the modified Gaussian message transfer iterative detection method, the Gaussian message transfer iterative detection method has certain convergence when the number of users is less than the number of antennas of the MU-MIMO system, and the convergence speed is higher.

Description

technical field [0001] The invention belongs to the technical field of communication, and further relates to a Gaussian message passing iterative detection method of a multiuser multiple-input multiple-output MU-MIMO (Multiuser Multiple-Input Multiple-Output) system in the technical field of wireless communication channel transmission. The invention can be used to decode user messages in a multi-user multiple-input multiple-output MU-MIMO system. Background technique [0002] Multi-user multiple-input multiple-output MU-MIMO system will be a very important communication system in future wireless communication. Multi-user multiple-input multiple-output MU-MIMO can significantly improve the throughput and greatly reduce the energy consumption, so it can meet the high throughput and high service quality requirements of the next generation multi-user wireless communication system . [0003] The efficient multi-user multi-input multi-output MU-MIMO system detection algorithm is...

AI Technical Summary

Problems solved by technology

However, the shortcomings of this method are that the factor graph detection method that only contains variable nodes has higher computational complexity and higher mean square error of

The disadvantage of this method is that when the message is transmitted, the mean and variance of the signal are directly transmitted without correction of the mean and variance. The speed is slow and cannot be used in practical multi-user multiple-input multiple-output MU-MIMO systems

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