5G multi-system coexistence resource allocation method under unlicensed spectrum based on Q learning

A resource allocation, multi-system technology, applied in electrical components, wireless communication, network planning, etc., can solve the problem of inability of NR-U system and WiFi system to coexist, and achieve the effect of improving spectrum resource utilization

Active Publication Date: 2020-04-24
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0006] The purpose of the present invention is to solve the technical defect that the NR-U system and the WiFi system cannot coexist without constraints o

Method used

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  • 5G multi-system coexistence resource allocation method under unlicensed spectrum based on Q learning
  • 5G multi-system coexistence resource allocation method under unlicensed spectrum based on Q learning
  • 5G multi-system coexistence resource allocation method under unlicensed spectrum based on Q learning

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Example Embodiment

[0057] Example 1

[0058] When the Q-learning-based 5G multi-system coexistence resource allocation method under unlicensed spectrum is implemented, it is based on figure 1 The scene shown. Such as figure 1 Description, there are 2 UEs in the NR-U system and 2 STAs in the WiFi system. Without loss of generality, in specific implementation, 10 UEs and 8 STAs share the same unlicensed spectrum resource.

[0059] However, because the NR-U system uses a centralized scheduling MAC mechanism, it has a better interference tolerance. The WiFi system uses a competition-based MAC mechanism. When the optimization goal is to maximize the throughput of the coexistence system, the resources of the unlicensed frequency band will be allocated to the NR-U system as much as possible, resulting in the failure of WiFi access Channel for communication, the throughput of the WiFi system is greatly reduced. In addition, in the coexistence system model, the NR-U system occupies the entire unlicensed f...

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Abstract

The invention relates to a 5G multi-system coexistence resource allocation method under an unlicensed spectrum based on Q learning, and belongs to the technical field of spectrum allocation in wireless communication. The method comprises the following steps: step 1, calculating throughputs of an NR-U system and a WiFi system in a coexistence scene, and respectively determining demands of the NR-Usystem and the WiFi system for spectrum resources; 2, calculating the optimal ABS number in the coexistence scene, specifically, determining a target function of the optimal ABS number in the coexistence scene; traversing the q values in sequence so as to find the q value meeting the optimization target, and calculating the number of the ABS according to the calculated q value: NABS = (1-q)T, wherein T is the length of one radio frame in the 5G NR system; 3, matching the ABS position in the coexistence scene, and realizing the matching of the WiFi system and the ABS position by using Q learning. According to the method, the total throughput of the heterogeneous network system is effectively improved while the fairness of the system is ensured; and the spectrum resource utilization rate ofthe coexistence system is effectively improved.

Description

technical field [0001] The invention provides a Q-learning-based 5G multi-system coexistence resource allocation method under license-free spectrum, which belongs to the technical field of spectrum allocation in wireless communication. Background technique [0002] Mobile communication is about to enter the fifth generation era, and emerging services based on 5G networks, such as interactive games, virtual / augmented reality technology, and telemedicine services, are emerging in a blowout manner. At the same time, with the rapid development and popularization of new technologies such as the global industrial Internet or the Internet of Things, the requirements for industrial technology upgrades are much higher than those for traditional Internet or Internet of Things applications. In order to cope with the explosive growth of massive data, how to scientifically plan and efficiently use spectrum resources to increase network capacity is an important way to solve this problem. ...

Claims

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Application Information

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IPC IPC(8): H04W16/10H04W16/14
CPCH04W16/14H04W16/10
Inventor 曾鸣唐清清费泽松王璐王文欣
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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