Solving Power Allocation Algorithm in Cognitive Radio Based on Reinforcement Learning

Abstract

The invention discloses a power allocation algorithm based on reinforcement learning to solve cognitive radio, S1, setting the initial value parameters of the deep learning algorithm, S2, setting the scene model of the CR-NOMA system, and setting the initial state and action State collection; S3, when a certain calculation moment t is less than or equal to the maximum limit time value T max When , obtain the state value at time t and calculate the corresponding reward function, and calculate the TD error δ t ; S4. Select the user's next action based on the value function, and use the learning rate and the TD error value function to update the initial value function to Q(s t ,a t )←Q(s t ,a t )+η c δ t ; Then get the corresponding reward according to the selected execution action, and obtain the policy function π(g), and then update it to π(s t ,a t )←π(s t ,a t )‑η a δ t ;π(g); S5. According to step S3, the TD error value is minimized, iteratively updated, and finally the maximum reward function value is obtained, that is, the allocation algorithm ends. It solves the problem in the prior art that power allocation cannot be well performed under the premise of incomplete channel information.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a power allocation strategy, which can be used to solve the power allocation problem in an underlay cognitive radio network. Background technique [0002] Overlay cognitive radio networks can solve the problem of spectrum scarcity, that is, under the constraint that the interference caused by cognitive users cannot degrade the service quality of primary users, cognitive users can use the same spectrum to transmit simultaneously with primary users. On the other hand, Non-orthogonal Multiple Access (NOMA), as a potential technical challenge to improve the spectrum efficiency of future wireless networks, has fundamentally changed the design of conventional access technologies . Power domain non-orthogonal multiple access technology (Power-domain NOMA) is one of the most popular technologies in NOMA technology. Its core idea is to explore the power domain differenc...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a power allocation algorithm based on reinforcement learning to solve cognitive radio, so as to solve the problem that power allocation cannot be performed well under the premise of incomplete channel information in the prior art

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