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Multi-user Subcarrier Power Allocation Method Based on Deep Reinforcement Learning

A technology of subcarrier power and reinforcement learning, applied in the field of communication, can solve problems such as resource shortage, achieve the effects of reducing signaling overhead, ensuring security, and overcoming the shortage of spectrum resources

Active Publication Date: 2021-05-28
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] Based on this, it is necessary to provide a multi-user subcarrier power allocation method based on deep reinforcement learning, electronic equipment and storage media to solve the problem of resource shortage

Method used

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  • Multi-user Subcarrier Power Allocation Method Based on Deep Reinforcement Learning
  • Multi-user Subcarrier Power Allocation Method Based on Deep Reinforcement Learning
  • Multi-user Subcarrier Power Allocation Method Based on Deep Reinforcement Learning

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Embodiment Construction

[0020] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0021] figure 1 A schematic diagram showing an application scenario of an embodiment of the present application, which is a D2D (Device-to-Device, device-to-device communication) under a cellular network, developed by 3GPP (3rd Generation Partnership Project, 3rd Generation Partnership Project) A schematic diagram of the application scenario proposed by the organization to allow LTE (Long Term Evolution, long-term evolution) terminals to communicate directly using cell resources without basic network facilities under the control of the communication system. Within the cov...

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Abstract

A multi-user subcarrier power allocation method, electronic equipment, and storage medium. The method in one embodiment includes: acquiring a current environment state, where the current environment state includes: a local state of a transmitter, a state of a base station, an interfering neighbor state, and an interfered neighbor state; Process the current environment state based on the first neural network used for action selection to obtain a current power allocation scheme, the first neural network includes action selection parameters; the current power allocation scheme includes: each available subcarrier, and the transmit power level corresponding to each available subcarrier. This embodiment ensures the security of information transmission to the greatest extent, realizes multiplexing of subcarriers, and can effectively overcome the problem of spectrum resource shortage.

Description

technical field [0001] The present application relates to the field of communication technology, in particular to a multi-user subcarrier power allocation method based on deep reinforcement learning, electronic equipment and storage media. Background technique [0002] With the development of communication networks and the advent of the era of the Internet of Things, the number of terminals connected to the communication network is increasing exponentially. It is estimated that more than 50 billion devices will be connected and exchange information with each other. In this case, with the access With the increase of the number of devices in the communication network, the demand for communication resources is huge. However, the spectrum resources that can be allocated are limited, and it is difficult to meet the demand for spectrum resources faced by the development of communication networks. Therefore, the shortage of spectrum resources has become a development bottleneck in ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W72/04H04W72/08H04W16/14G06N3/04G06N3/08H04W72/54
CPCH04W72/0473H04W72/0453H04W16/14G06N3/08G06N3/045H04W72/53H04W72/541
Inventor 古博林梓淇张旭丁北辰韩瑜
Owner SUN YAT SEN UNIV