Unmanned aerial vehicle assisted edge computing resource allocation method based on radio frequency energy collection

A technology of edge computing and radio frequency energy, applied in network traffic/resource management, mechanical equipment, wireless communication, etc.

Active Publication Date: 2021-03-16
FUZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the purpose of the present invention is to provide a resource allocation method for UAV-assisted edge computing based on radio frequency energy collection to solve the problem that the computing task requ

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  • Unmanned aerial vehicle assisted edge computing resource allocation method based on radio frequency energy collection
  • Unmanned aerial vehicle assisted edge computing resource allocation method based on radio frequency energy collection
  • Unmanned aerial vehicle assisted edge computing resource allocation method based on radio frequency energy collection

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Embodiment Construction

[0070] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0071] Please refer to image 3 , the present invention provides a resource allocation method based on radio frequency energy harvesting of unmanned aerial vehicles to assist edge computing, comprising the following steps:

[0072] Step S1: build the MEC system network structure of radio frequency energy collection; figure 1 As shown, including UAV, base station BS1, base station BS2, user equipment and TV tower;

[0073] The edge server is deployed on the UAV and the base station BS1, which can provide users with MEC services. The base station and users are located on the ground, and the UAV is deployed near the base station BS1 at a fixed height H to assist the base station BS1 in processing user computing tasks.

[0074] Base stations BS1 and BS2 are powered by traditional power grids, and end users i (i=1, 2,...I) are equipped with energy harvest...

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Abstract

The invention relates to a radio frequency energy collection-based unmanned aerial vehicle assisted edge computing resource allocation method, and the method is characterized by comprising the following steps: S1, constructing a radio frequency energy collection MEC system network structure; S2, calculating total energy collected by a user from a remote environment radio frequency source; S3, acquiring transmission time delay required for unloading the calculation task to the unmanned aerial vehicle or the base station; S4, calculating the energy consumption of the user task unloaded to the unmanned aerial vehicle or the base station; S5, obtaining calculation time delay required for executing a system user calculation task; S6, calculating the energy consumption of a user calculation taskof the execution system; S7, constructing preset constraints of energy consumption, computing resources, subcarrier proportionality coefficients and transmitting power; S8, according to preset constraints, constructing an optimization model for minimizing system energy consumption; S9, solving an optimal distribution result of the system by adopting a method of combining a genetic algorithm and nonlinear programming, and obtaining an energy consumption value of the system.

Description

technical field [0001] The present invention relates to the fields of wireless communication technology and mobile edge computing, in particular to a resource allocation method for UAV-assisted edge computing based on radio frequency energy collection. Background technique [0002] With the rapid development of the Internet of Things, mobile users can now personally experience various emerging smart applications, enjoy the convenience brought by face recognition and smart home, and the high-quality services of mobile online games and augmented reality, but these smart The application is very sensitive to delay, has high requirements on delay, and has a large amount of data to be processed. Therefore, mobile users are required to have great computing power and be able to process large amounts of data in a timely manner. However, mobile devices have limited size, limited battery capacity, and low computing power, so it is very challenging for mobile devices to execute these a...

Claims

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Application Information

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IPC IPC(8): H04W24/02H04W24/06H04W28/16
CPCH04W24/02H04W24/06H04W28/16Y02T10/40Y02D30/70
Inventor 赵宜升陶丽佳徐新雅陈加法许志猛
Owner FUZHOU UNIV
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