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Universal grouping method for users in non-orthogonal multiple access based on machine learning

A non-orthogonal multiple access, machine learning technology, applied in the field of user general grouping, can solve problems such as combinatorial explosion, and achieve the effect of increasing the number of user accesses, improving system communication capacity, and taking into account computational complexity and effectiveness.

Active Publication Date: 2020-12-11
TONGJI UNIV
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  • Abstract
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Problems solved by technology

On the other hand, the consideration of overlapping groups will lead to combinatorial explosion, and solving the optimal overlapping grouping is an NP-hard problem

Method used

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Embodiment Construction

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0043] A method for general grouping of users in non-orthogonal multiple access based on machine learning, the process of which is as follows figure 1 shown, including:

[0044] Step 1: Obtain the transmit power budget and channel gain coefficient data of all users in the system;

[0045] Step 2: Build a multi-user group communication model;

[0046] Specifically: there are k users and one base station in the entire communication system, multiple users f...

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Abstract

The invention relates to a universal grouping method for users in non-orthogonal multiple access based on machine learning. The universal grouping method comprises the following steps: 1, acquiring transmitting power budget and channel gain coefficient data of all users in a system; 2, constructing a multi-user packet communication model; 3, solving the multi-user packet communication model to obtain a power optimization closed-form solution and a user packet solution; and 4, grouping the users according to the user grouping solution, and performing power control through a power optimization closed-form solution to complete universal grouping of the users. Compared with the prior art, the method has the advantages of realizing user overlapping grouping, improving user access amount, considering calculation complexity and effectiveness and the like.

Description

technical field [0001] The invention relates to the technical field of intelligent information collection, in particular to a general user grouping method in non-orthogonal multiple access based on machine learning. Background technique [0002] With the continuous depletion of limited spectrum resources, the problem of multiple access in 5G and future practical communication systems is very challenging. On the other hand, the Internet of Things (IoT) has become a unique network system, in which various small components and sensors can independently generate sensory information and network traffic, how to effectively collect sensory information distributed over a large area , is a new challenge. Facing the access requirements of large-scale users or sensors, multiple access technology needs to be improved urgently. Non-orthogonal multiple access (NOMA) technology, because it can multiplex multiple users in the frequency domain and multiplex resources such as frequency / time...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W16/14H04W28/16H04W48/16H04W52/34
CPCH04W16/14H04W28/16H04W52/34H04W48/16Y02D30/70
Inventor 赵生捷陈伟超张荣庆肖京丁富强张林
Owner TONGJI UNIV
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