Design of JiuTian Intelligent Network Simulation Platform

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.