Processing resource allocation method under centralized base station architecture

Abstract

The invention provides a method for allocating processing resources under a centralized base station architecture. The method includes: obtaining the computing resource demand of virtual base station i to be allocated resources, wherein i represents the virtual base station number, and M represents the number of virtual base stations to be allocated resources; obtaining the remaining resources of each processor core in the protocol processing resource pool and Build an allocatable processor core set, expressed as wherein, j represents the number of the processor core, S represents the total number of processor cores in the protocol processing resource pool, and represents the remaining resource amount of the processor core j; from the allocatable A processor core is allocated to the virtual base station i in the processor core set to perform resource processing. The present invention takes the processor core as the granularity of resource allocation and optimizes the resource allocation scheme with the aim of minimizing power consumption, which can improve resource utilization and reduce operating power consumption.

Description

technical field [0001] The present invention relates to the technical field of wireless communication, in particular to a method for allocating processing resources under a centralized base station architecture. Background technique [0002] With the rapid development of mobile communication technology and the dramatic increase in the number of mobile smart terminals, the service demands of mobile users are constantly increasing, and mobile data traffic is experiencing explosive growth. The disadvantages and limitations of the traditional mobile network architecture are gradually revealed. The traditional mobile communication architecture is centered on the base station of the cell. The base stations are independent of each other. The resources between the base stations cannot be shared with each other, resulting in overloading of the busy base stations. Idle resources are not utilized, resulting in an extremely low resource utilization rate of the global mobile network, was...

AI Technical Summary

Problems solved by technology

[0004] At present, the allocation or dynamic adjustment methods for base station processing resources usually include the following: First, maximize the number of base stations that can be served by the system resource pool. This algorithm assumes that each base station is in the maximum load state. In the actual system, the base station The load changes dynamically over time, and this allocation scheme leads to the waste of some computing resources

Second, based on the resource allocation method of the baseband pool, periodically obtain the resource utilization rate of the cell, the resource low load threshold and the resource high load threshold, and make a judgment based on the resource utilization rate of the cell, as well as the resource low load threshold and the resource high load threshold, According to the judgment result, the cells in the baseband pool are grouped, and then the resources are allocated. In this scheme, the grouping of cells is fixed, and it is difficult to adapt to the scenario where a large number of dynamic changes in cell load occur.

Third, the processor-based computing resource allocation scheme, which first obtains the set of services to be allocated, then divides the scheme based on the computing resource mapping, arranges and combines the available computing resource blocks according to the predetermined strategy, and obtains different combinations of computing resource blocks, and finally Allocate computing resource block combinations for the services in the service set to be allocated. This scheme can effectively improve the utilization of computing resources in the communication system, but does not consider the energy consumption of the processor.

[0005] In short, in the existing base station processing resource allocation scheme, the granularity of the allocated computing resources is a computing physical device (such as an IT server) or a computing processor. If the resource allocation granularity is too large, the utilization rate of computing resources will be reduced and the energy consumption will be reduced. increase, and in the prior art, the energy consumption of alternative resource allocation schemes is not considered, and resource allocation is optimized with the goal of minimizing energy consumption, which further leads to an increase in energy consumption

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