An intelligent decision-making method for data packet transmission based on deep reinforcement learning

Abstract

The invention relates to an intelligent decision-making method for data packet transmission based on deep reinforcement learning, including: constructing a deep neural network model; designing and initializing state space and behavior space; obtaining current state information and historical state information of data transmission, and inputting state space; adopting The experience playback mechanism saves historical state information; iteratively executes steps (3) and (4) T times, and the round ends; updates the target value neural network parameter θ′, and assigns the latest parameter θ of the original value neural network to the target value neural network ; Iteratively execute steps (2) to (5) until the number of iterations reaches the preset round upper limit N or the deep neural network converges, then terminate and automatically obtain a data transmission strategy that satisfies multiple constraints and lower energy consumption. The invention improves the service quality of users, reduces the energy consumption of data transmission at the same time, and effectively improves the intelligent decision-making ability of data transmission in a communication network in a highly complex and dynamic environment.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to an intelligent decision-making method for data packet transmission based on deep reinforcement learning. Background technique [0002] With the development of the Internet of Things and the large-scale popularization of mobile terminals, wireless traffic has surged, and energy consumption caused by data transmission has also increased significantly. In addition, with the introduction of new concepts such as green networks and smart networks, reducing energy consumption has become increasingly important. How to reasonably formulate data transmission strategies to achieve stable data transmission and reduce transmission energy consumption while ensuring user service experience has become a topic of great concern. [0003] Data transmission in the current context is becoming complex, diverse and dynamic, and data transmission decisions are faced with the test of a hu...

AI Technical Summary

Problems solved by technology

At the same time, considering the uncertainty of the data packet size and the number of requests, as well as the strong demand of users for transmission delay, traditional algorithms cannot comprehensively consider many constraints and reduce transmission energy consumption when dealing with such complex and dynamic data transmission requirements. , it is difficult to obtain the ideal optimization effect

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