User clustering and resource allocation optimization method and system, medium, equipment and application

Abstract

The invention belongs to the technical field of wireless communication, and discloses a user clustering and resource allocation optimization method. In a non-orthogonal multiple access-based edge computing system, through collaborative optimization of user clustering, computing resource block allocation and sending power control strategies, as many users as possible are accommodated and the total energy consumption of the users and an MEC server is reduced as much as possible under the condition of ensuring QoS requirements of user task processing time delay. According to the invention, the non-orthogonal multiple access is introduced into a mobile edge computing system, so that the problems of small system capacity caused by wireless resource shortage in the mobile edge computing system and low data transmission rate in the computing unloading process caused by low spectrum utilization rate are relieved, the sending energy consumption of mobile equipment in the computing unloading process is reduced, and the number of users accommodated by the system is increased; the energy consumption of the MEC server is reduced when the MEC server is inconvenient to connect with a power supply, and the working time of the MEC server is prolonged; a heuristic optimization algorithm is low in complexity and can be applied to an actual system.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method, system, medium, device and application for optimizing user clustering and resource allocation. Background technique [0002] Currently: Mobile Edge Computing (MEC) technology can effectively solve the problem of insufficient device processing capacity and greatly improve energy efficiency by offloading computing and energy-intensive tasks on user equipment to MEC servers. Non-Orthogonal Multiple Access (NOMA) can greatly improve wireless spectrum efficiency and accommodate more users by allowing multiple users to use the same wireless resources at the same time. [0003] Due to the limitation of battery capacity of user equipment or IoT devices, the reduction of energy consumption or the improvement of energy efficiency is the main research goal in NOMA-based MEC system research, and user clustering and resource allocation are the main optimiz...

AI Technical Summary

Problems solved by technology

When the MEC server is a rechargeable server, in addition to the energy consumption of the user, the energy consumption of the MEC server also needs to be considered. However, the existing literature does not consider this situation, and there is a lack of theoretical support for this scenario.

In addition, the problems involving the above-mentioned optimization approaches are often non-convex, so it is difficult to solve or the solution complexity is too high to be applied in practice. Low-complexity heuristic algorithms are easier to implement and thus easier to apply in practice.

[0004] Through the above analysis, the existing problems and defects of the existing technology are: the existing literature does not consider the case that the MEC service area is a charging server, and the problems related to the optimization method are often non-convex, so it is difficult to solve

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