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Millimeter wave large-scale MIMO-NOMA system resource allocation method and system

A MIMO-NOMA, system resource technology, applied in the field of millimeter wave massive MIMO-NOMA system resource allocation, can solve the problems of resource system performance impact, limited wireless resources, etc.

Active Publication Date: 2021-08-10
INNER MONGOLIA UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, with the ultra-dense deployment of base stations and the large-scale interconnection of user terminals, the number of links between base stations and users and the data transmission rate have increased sharply, and the wireless resources of the system have become relatively limited. Unreasonable allocation of resources will affect system performance. impact, bringing new challenges to mmWave massive MIMO-NOMA networks

Method used

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  • Millimeter wave large-scale MIMO-NOMA system resource allocation method and system
  • Millimeter wave large-scale MIMO-NOMA system resource allocation method and system
  • Millimeter wave large-scale MIMO-NOMA system resource allocation method and system

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Embodiment 1

[0028] like figure 2 As shown, the present application provides a resource allocation method for a millimeter-wave massive MIMO-NOMA system, including the following steps:

[0029] Step S210, the base station obtains the current state s of the system t , and the current state s t As the input of the DQN neural network, the current sub-channel allocation action a is obtained t1 and the current power allocation action a t2 ;

[0030] The DQN neural network can obtain the best action to be taken according to the state of the current system, so as to ensure that the reachability and rate of the entire MIMO-NOMA system are maximized under the minimum data rate constraint of the user.

[0031] In order to achieve this goal, the state s of the system at the tth time slot t Defined as: s t ={SINR l,m,k (t)}, and s t ∈s, where s is the state space of the system, SINR l,m,k (t) is the SINR of the kth user in the mth group on the lth subchannel at the tth time slot. Among them...

Embodiment 2

[0052] Such as image 3 with Figure 4 , the application provides a millimeter wave massive MIMO-NOMA system resource allocation method, comprising the following steps:

[0053] Step S310, the base station obtains the current state s of the system t , and the current state s t As the input of DuelingDQN neural network and DDPG neural network, get the current sub-channel allocation action a t1 and the current power allocation action a t2 ;

[0054] The state s of the system at the tth time slot t defined as s t ={SINR l,m,k (t)}, and s t ∈s, where s is the state space of the system, SINR l,m,k (t) is the SINR of the kth user in the mth group on the lth subchannel at the tth time slot. Among them, the system state s t ={SINR l,m,k (t)} reflects the current channel quality SINR of the link, subchannel allocation factor x l,m,k (t) and the current power allocation factor P l,m,k (t).

[0055] The base station obtains the current state of the system s t , for the Du...

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Abstract

The invention relates to the technical field of signal communication, in particular to a millimeter wave large-scale MIMO-NOMA system resource allocation method and system, and the method comprises the steps: a current state of a system is taken as as the input of a DQN neural network, and a current action is obtained; the base station executes the current action, selects power and sub-channels according to the current action and sends the power and the sub-channels to all users so as to distribute the sub-channels and the power, updates the environment of the system, feeds back the distributed action according to a set reward function, feeds back a reward feedback value to the base station, and obtains the current reward feedback value, and the state of the system at the next moment; and the base station trains a DQN neural network according to the current reward feedback value and the state of the system at the next moment, and obtains a sub-channel allocation action at the next moment and a power allocation action at the next moment so as to carry out the next round of channel and power allocation. According to the method and the device, wireless resources can be reasonably and efficiently allocated to each user under the conditions of limited resources and higher data rate requirements of the users.

Description

technical field [0001] The present application relates to the technical field of signal communication, and in particular to a resource allocation method and system for a millimeter wave massive MIMO-NOMA system. Background technique [0002] In recent years, with the commercialization of 5G and the exponential growth of smart devices and applications, the corresponding urgent requirements for high data rates have increased dramatically. To meet these requirements, sixth generation (6G) wireless communication is being extensively studied by academia and industry. Compared with the existing 5G, the 6G communication network can fundamentally achieve a data rate of 10-100 times, support a larger-scale interconnection, the minimum data rate reaches 1Gbps, and the peak data rate is higher than 100Gbps. [0003] Since the mmWave massive MIMO technology can provide greater bandwidth and higher spectral efficiency, which can significantly improve the achievable data rate performance...

Claims

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Application Information

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IPC IPC(8): H04W72/04H04B7/0426G06N3/08G06N3/04
CPCH04W72/0453H04W72/0473H04B7/0426G06N3/04G06N3/084
Inventor 刘洋李玉婷张颖慧宋凯鹏董娜客华美
Owner INNER MONGOLIA UNIVERSITY