Distributed dynamic spectrum access method based on multi-agent reinforcement learning

Abstract

The invention discloses a distributed dynamic spectrum access method based on multi-agent reinforcement learning, and the method enables a multi-user distributed dynamic spectrum access problem to be modeled into a multi-agent Markov cooperative game model, and constructs a centralized training and distributed execution multi-agent reinforcement learning framework. The multi-agent reinforcement learning framework comprises an offline training module and an online execution module, the online execution module performs spectrum access of the cognitive user by using a learned access strategy, and the offline training module dynamically updates the online execution module according to a spectrum access result of the cognitive user. The invention provides a multi-user cooperative spectrum access method with self-adaptive communication environment and extensible network scale, which reduces access conflicts among cognitive users while avoiding interference to authorized users, thereby maximizing the access success rate of the cognitive users and improving the utilization efficiency of the spectrum.

Description

technical field [0001] The invention relates to the technical field of wireless communication networks, in particular to a distributed dynamic spectrum access method and system based on multi-agent reinforcement learning. Background technique [0002] In cognitive wireless networks, cognitive users use the overlay method to opportunistically access spectrum holes of authorized users for data transmission. Distributed multi-user dynamic spectrum access faces two major challenges: one is to avoid the interference of cognitive users to the primary user, that is, when the primary user occupies the licensed spectrum for data transmission, the cognitive user cannot access the corresponding spectrum; the other is Avoid access conflicts between cognitive users, that is, prevent more than two cognitive users from accessing the same spectrum hole, resulting in unsuccessful data transmission. Due to the limited perception ability of a single cognitive node, only part of the channel st...

AI Technical Summary

Problems solved by technology

[0003] The present invention provides a distributed dynamic spectrum access method and system based on multi-agent reinforcement learning, which is used to overcome the interference of the primary user during data transmission when the cognitive user has the opportunity to access the spectrum hole of the authorized user in the prior art , at the same time, there will be access conflicts between cognitive users, which will lead to defects such as low throughput of the communication system

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