Uplink signaling-free NOMA system multi-user detection method based on deep learning

Abstract

The invention discloses an uplink signaling-free NOMA system multi-user detection method based on deep learning. The method comprises the three steps of conducting modeling on received signals, conducting sparse representation on the received signals and training a deep structure for sparse signal recovery. According to the method, multi-user detection is conducted by using the structured compressed sensing theory by means of the sparsity of users in an NOMA system and the relation existing among transmitting signals of different time slots, the sparse reconstruction problem is solved by meansof the deep learning theory, low-complexity and high-performance multi-user detection can be achieved, and multi-user detection is achieved by using the structured compressed sensing theory by combining the correlation of users among the transmitting signals of different time slots; and the underdetermined inverse problem of signal recovery is solved by means of the deep learning theory, and thereconstruction precision and the reconstruction efficiency of a sparse reconstruction algorithm are improved from the three aspects including parameter optimization, sparse representation training andneural network training on the basis of the deep learning method.

Description

technical field [0001] The invention relates to a multi-user detection method of an uplink signaling-free NOMA system based on deep learning, and belongs to the field of electronic technology. Background technique [0002] With the popularization and application of smart terminals, the rapid development of the Internet of Things (IoT), the explosion of artificial intelligence and big data, and the continuous growth of new mobile business demands, the demand for wireless transmission rates is also increasing exponentially, and the transmission rate of wireless communications will be difficult to meet future communications application requirements. Non-orthogonal multiple access (NOMA), as one of the key technologies of the fifth-generation mobile communication (5G), can use spectrum resources more efficiently while meeting user experience requirements, and provide Therefore, the research on the NOMA system has received extensive attention. [0003] In order to obtain commun...

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Problems solved by technology

[0005] At present, structured compressed sensing and deep learning technologies are rarely used in multi-user detection, and no relevant patents have been disclosed for the multi-user detection method of uplink signaling-free NOMA system based on deep learning

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