Spectrum resource management method based on deep reinforcement learning

Abstract

The invention discloses a spectrum resource management method based on deep reinforcement learning, and mainly aims to solve the problem that incomplete channel state information cannot be effectivelyutilized for spectrum and power allocation and spectrum resource management multitarget optimization in the prior art. According to the implementation scheme, the method comprises the following steps: constructing an adaptive deep neutral network which takes channel gain and noise power as weight parameters by taking spectrum efficiency maximization as an optimization target; and initializing theweight parameters, observing user access information and interference information, calculating a loss function according to the energy efficiency and fairness of a communication network, updating thechannel gain and the noise power layer after layer along the gradient descent direction of the loss function, repeatedly training the adaptive deep neural network, and outputting an optimal spectrumresource management strategy when a training end condition is satisfied. Through adoption of the spectrum resource management method, the optimal spectrum resource management strategy can be obtainedon the basis of the incomplete channel state information, and the spectrum efficiency, energy efficiency and fairness of the communication network are improved effectively. The spectrum resource management method can be applied to spectrum and power allocation in wireless communication.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a resource management method, which can be used for frequency spectrum and power allocation in wireless communication. Background technique [0002] With the rapid increase in the number of communication devices in the wireless network and the increasingly diverse business requirements, the wireless communication field is facing many technical challenges such as intelligence, broadband, diversification, and integration, resulting in increasing scarcity of spectrum resources. In addition, the complexity, diversity, and dynamics of the wireless network environment make it increasingly difficult to obtain channel state information. The introduction of new concepts such as green networks and smart networks has made the optimization goals of spectrum resource management increasingly diverse. Therefore, how to optimize spectrum utilization and maximize the efficient m...

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Problems solved by technology

[0008] It can be found that most of the existing spectrum resource management methods currently need to obtain the optimal spectrum resource management strategy based on complete channel state information, and the optimization objective is single, it is difficult to effectively solve the multi-objective optimization problem, and the multi-objective optimization problem is regarded as NP full question

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