Task unloading and resource allocation method based on D2D communication

Abstract

The invention discloses a task unloading and resource allocation method based on D2D communication, and belongs to the technical field of wireless communication. According to the method, it is assumedthat used users can be mutually unloaded, meanwhile, channel interference is considered, and modeling is carried out with the purpose of minimizing the total overhead of a system as the purpose, andthen the problem is decoupled into two sub-problems, the two sub-problems are respectively solved by utilizing pseudo-convex and convex optimization technologies, the two sub-problems are iterativelysolved, and finally an optimal solution of the problem is obtained. According to the method provided by the invention, the mutual unloading between the user equipment is considered, and the reasonablecalculation task is allocated to the user equipment according to the resources (calculation capability, residual electric quantity and the like) owned by the user equipment, so that the equipment with limited resources can participate in calculation, the resources are reasonably utilized, and the calculation performance of all users is improved. Besides, through interference management and powercontrol, channels are reasonably distributed to users, and D2D communication quality can be guaranteed.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method for task offloading and resource allocation based on D2D communication. Background technique [0002] The popularity of smart terminals and the vigorous development of mobile 5G networks have promoted the development of mobile computing applications, such as perceptual computing, interactive online games, etc., and these applications play a very important role in people's daily life. But these types of mobile computing applications are usually low-latency and require a lot of computing resources, which poses great challenges for resource-constrained mobile devices. In order to solve the contradiction between resource-demanding applications and mobile devices with limited resources, mobile edge computing (mobile edge computing) offloads complex computing tasks to servers with strong computing power to reduce delay and energy consumption. , is a...

AI Technical Summary

Problems solved by technology

However, when resource-rich users help resource-limited users to perform calculations, some of the resource-limited user devices are idle, resulting in waste of resources, and the goal of minimizing computing costs or maximizing benefits for all users has not been achieved.

Moreover, when users choose the best offloading decision for their computing tasks, different users may occupy the same channel, and will interfere with each other when they simultaneously transmit tasks

[0004] To sum up, most of the current research work only roughly divides devices into resource-constrained devices and resource-rich devices, and only considers task offloading from resource-constrained devices to resource-rich devices, without considering Computing on resource-constrained devices

In addition, most studies ignore the impact of transmission interference on task offloading decisions, channel allocation, and user transmission power.

Images