Design of JiuTian Intelligent Network Simulation Platform
Lei Zhao, Miaomiao Zhang, Guangyu Li, Zhuowen Guan, Sijia Liu, Zhaobin, Xiao, Yuting Cao, Zhe Lv, Yanping Liang

TL;DR
The paper presents the design of the JiuTian Intelligent Network Simulation Platform, a scalable system providing wireless communication simulation data and open services for reinforcement learning and optimization tasks.
Contribution
It introduces a comprehensive architecture and functionalities of a novel simulation platform supporting reinforcement learning and scenario-based optimization.
Findings
Provides scalable simulation functionalities
Enables reinforcement learning model training and inference
Supports parameter configuration updates for optimization
Abstract
This paper introduced the JiuTian Intelligent Network Simulation Platform, which can provide wireless communication simulation data services for the Open Innovation Platform. The platform contains a series of scalable simulator functionalities, offering open services that enable users to use reinforcement learning algorithms for model training and inference based on simulation environments and data. Additionally, it allows users to address optimization tasks in different scenarios by uploading and updating parameter configurations. The platform and its open services were primarily introduced from the perspectives of background, overall architecture, simulator, business scenarios, and future directions.
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Taxonomy
TopicsAdvanced Computational Techniques and Applications · Industrial Technology and Control Systems · Advanced Data Processing Techniques
