Mr. Yang Li Profile

Yang Li

at Beijing Fibrlink Communications Co., Ltd

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Proceedings Article | 9 October 2022 Paper

Dynamic resource allocation strategy for RAN network slices in smart grid

Yang Li, Yue Hou, Lijun Duan

Proceedings Volume 12246, 122461X (2022) https://doi.org/10.1117/12.2643740

KEYWORDS: Networks, Computer simulations, Signal to noise ratio, Telecommunications, Systems modeling, Data modeling, Wireless communications

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It is an urgent requirement for the development of smart grid to allocate resources effectively to satisfy the changing power service environment and the needs of power users. 5G network slices provide the solutions. For dynamically demands of resources in smart grids, reinforcement learning is introduced to address the resource allocation problem of RAN slices in this paper. The training process in reinforcement learning is divided into two stages: slice layer and user layer. The slice layer performs the action of resource allocation, and the user layer calculates and feeds back the reward of the action. This paper focuses on how resources in slices are allocated to users, that is, resource reallocation in the user layer stage. The evaluation function of quality of experience (QoE) is defined, and a fair allocation algorithm that maximizes the utility of QoE to improve the experience quality of user is proposed. The simulation comparison results indicate that our algorithm combined with reinforcement learning not only improves the resource utilization, but also maximizes the user's QoE, which has obvious advantages over other methods. Moreover, the training cost of reinforcement learning is reduced and the convergence speed is accelerated.

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