A multi-user detection method based on cross-validation for non-orthogonal multiple access systems

Abstract

The invention belongs to the technical field of wireless communication signal detection, and relates to a non-orthogonal multi-access system multi-user detection method based on cross validation. The non-orthogonal multi-access system multi-user detection method based on cross validation comprises the steps of extracting part of received data, and regarding the part of received data as a criterion for judging whether sparsity is estimated precisely, so as to realize more precise estimation of the sparsity. Since a spread spectrum sequence of each user is composed of pseudo random Gaussian sequences and has high irrelevance, the small amount of data can be extracted to ensure the successful recovery of signals when ensuring that data used for recovering the signals is sufficient; due to the high irrelevance, the spread spectrum sequences of the users are equivalent in weight when being used for recovering the signals, thus the data used for recovering the signals can be reserved randomly as long as the precondition of sufficient data volume is guaranteed. The non-orthogonal multi-access system multi-user detection method based on cross validation has little influence on data recovery, greatly improves the precision of user activeness estimation, and can significantly improve the SER performance of the detection algorithm.

Description

technical field [0001] The invention belongs to the technical field of wireless communication signal detection, and relates to a multi-user detection method based on cross-validation non-orthogonal multiple access system. Background technique [0002] Large-scale machine communication is one of the core application scenarios of 5G in the future. It has the characteristics of small packet transmission, massive connections, low-latency access, and low power consumption. Existing multiple access technology has been difficult to meet the requirements of mass connection and high scalability of large-scale machine communication, non-orthogonal multiple access technology is considered to be a more suitable solution; at the same time, the uplink of large-scale machine communication is generally There is a characteristic of sporadic communication, that is, the number of users accessing the base station at a certain moment is much smaller than the total number of users. Due to the ma...

AI Technical Summary

Problems solved by technology

Aiming at the problem that the iterative stop condition of the sparsity estimation is not easy to choose, the present invention divides the received data into two parts: the first part is the recovery of the user transmission signal, and the second part is used to test whether the sparsity estimation is accurate, that is, the data itself Find a suitable iteration termination condition instead of artificially setting the sparsity estimation iteration termination condition

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