Data packet transmission intelligent decision-making method based on deep reinforcement learning

A technology of reinforcement learning and intelligent decision-making, applied in the field of wireless communication, it can solve problems such as difficult optimization effects, and achieve the effect of improving intelligent decision-making ability, solving poor optimization effects, and ensuring stable transmission.

Active Publication Date: 2021-01-22
ANHUI UNIV OF SCI & TECH
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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 comprehensivel

Method used

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  • Data packet transmission intelligent decision-making method based on deep reinforcement learning
  • Data packet transmission intelligent decision-making method based on deep reinforcement learning
  • Data packet transmission intelligent decision-making method based on deep reinforcement learning

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Embodiment Construction

[0039] Such as figure 2 As shown, an intelligent decision-making method for data packet transmission based on deep reinforcement learning, the method includes the following sequential steps:

[0040] (1) Construct a deep neural network model, which includes an original value neural network for calculating the behavioral value function, and a target value neural network for behavior selection based on the calculation results of the behavioral value function;

[0041] (2) Design and initialize state space and behavior space;

[0042] (3) Obtain the current state information and historical state information of data transmission, enter the state space, and optimize and allocate the transmission order and transmission power of data packets;

[0043] (4) Use the experience playback mechanism to save historical state information, and randomly collect training samples for deep neural network training;

[0044] (5) According to the total number of data packets T, step (3) and step (4)...

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Abstract

The invention relates to a data packet transmission intelligent decision-making method based on deep reinforcement learning. The method comprises the following steps: constructing a deep neural network model; designing and initializing a state space and a behavior space; acquiring current state information and historical state information of data transmission, and inputting the current state information and the historical state information into a state space; storing historical state information by adopting an experience playback mechanism; iteratively executing the step (3) and the step (4) for T times, and ending the round; updating the target value neural network parameter [theta]', and endowing the target value neural network with the latest parameter theta of the original value neuralnetwork; and (3) iteratively executing the steps (2) to (5) until the number of iterations reaches a preset round upper limit N or the deep neural network is converged, and terminating and automatically obtaining a data transmission strategy which meets the multi-constraint condition limitation and is lower in energy consumption. According to the invention, the user service quality is improved, the data transmission energy consumption is reduced, and the intelligent decision-making capability of data transmission of a communication network in a highly complex dynamic environment is effectively improved.

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...

Claims

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Application Information

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IPC IPC(8): H04W72/04G06N3/04G06N3/08
CPCG06N3/08G06N3/045H04W72/53Y02D30/70
Inventor 葛斌李孜恒方贤进杨高明
Owner ANHUI UNIV OF SCI & TECH
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