Network slice dynamic resource scheduling method combining congestion control and resource allocation under H-CRAN network

Abstract

The invention relates to a network slice dynamic resource scheduling method combining congestion control and resource allocation under an H-CRAN network, and belongs to the technical field of mobile communication. The method comprises considering service access control, congestion control, wireless resource allocation and multiplexing comprehensively; and dynamically allocating spectrum and powerresources to the network slice users with different performance requirements in each resource scheduling time slot by taking maximization of network average and throughput as a target, and controllingthe new service data volume accessed by each terminal user in the current time slot. According to the congestion control and resource allocation combined network slice dynamic resource scheduling method provided by the invention, the overall throughput of the network can be improved on the basis of meeting the service quality requirement of each slice user, and the dynamic balance between the time delay and the throughput can be realized by adjusting the value of the control parameter.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and relates to a network slicing dynamic resource scheduling method for joint congestion control and resource allocation under the H-CRAN network. Background technique [0002] According to Cisco's 11th VNI global mobile data traffic forecast, by 2021, the global monthly mobile service data volume will reach 49EB, and machine-to-machine connections will account for 29% of the total mobile connections. Mobile operators expect to provide subversive speed, ultra-low latency and dynamic configuration capabilities through next-generation networks to meet growing user needs, better support emerging application cases such as augmented reality, Internet of Things and smart medical care, and achieve shared Diverse application scenarios with different performance requirements coexist in the underlying physical network, so as to better cater to new service trends across mobile, residential and ...

AI Technical Summary

Problems solved by technology

[0006] Although many research works have deeply explored network slicing technology and H-CRAN architecture, most of the research content discusses the two separately, and few explore the potential performance advantages of the combination of network slicing and H-CRAN. Considering the coexistence of application scenarios with different performance requirements under the H-CRAN network, there is a lack of an efficient dynamic resource allocation scheme based on network slicing under the H-CRAN network

Secondly, most of the previous research work explored the problem of optimizing the instantaneous performance index of the wireless network in the fixed network environment, that is, single-slot optimization. not much work

In addition, most of the research work is based on the assumption of full buffer (full-buffer), ignoring the randomness and burstiness of business traffic arrival, then when the business data arrives too much, the network will be congested

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