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RANFusion: A Comprehensive Tool for Simulating Handover In Next-G RAN

Seyed Bagher Hashemi Natanzi, Bo Tang

TL;DR

RANFusion tackles the critical need for scalable, realistic handover simulation in 6G/O-RAN by delivering a cross-platform, JSON-configured RAN simulator with an E2-like interface and xApp/rApp API access. Its architecture combines configurable network setup, modular components (configuration management, traffic and database management, load balancing, AI-driven handover algorithms, and a command-line interface) to enable precise, repeatable experimentation of handover and load-balancing strategies. The work demonstrates practical benefits through experiments that show high handover success, controlled latency, and balanced sector and cell loads under varying traffic, validating the approach for RAN and O-RAN testing. By providing an extensible AI core and API-enabled testing workflow, RANFusion significantly aids researchers and operators in refining mobility management and resource optimization for open, disaggregated RAN ecosystems, with clear paths toward integration with RICs and broader OA-RAN testbeds.

Abstract

The rapid advancement of 5G networks and the upcoming transition to 6G necessitate the use of the Open Radio Access Network (O-RAN) architecture to enable greater flexibility, interoperability, and innovation. This shift towards 6G and O-RAN requires the development of advanced simulation tools for testing, analyzing, and optimizing Radio Access Network (RAN) operations. This need becomes critical due to the complex dynamics of mobility management inherent in the 6G vision and next-generation networks. These networks anticipate advanced handover methods for mobile users, UAVs, IoT devices, and beyond. Addressing this gap, this paper introduces RANFusion: a robust RAN simulator specifically created to explore a variety of handover scenarios and to test and balance resources between users. This tool enables precise simulations for refining handover strategies within RAN and O-RAN environments, thereby ensuring optimal performance and reliability in these advanced network infrastructures.

RANFusion: A Comprehensive Tool for Simulating Handover In Next-G RAN

TL;DR

RANFusion tackles the critical need for scalable, realistic handover simulation in 6G/O-RAN by delivering a cross-platform, JSON-configured RAN simulator with an E2-like interface and xApp/rApp API access. Its architecture combines configurable network setup, modular components (configuration management, traffic and database management, load balancing, AI-driven handover algorithms, and a command-line interface) to enable precise, repeatable experimentation of handover and load-balancing strategies. The work demonstrates practical benefits through experiments that show high handover success, controlled latency, and balanced sector and cell loads under varying traffic, validating the approach for RAN and O-RAN testing. By providing an extensible AI core and API-enabled testing workflow, RANFusion significantly aids researchers and operators in refining mobility management and resource optimization for open, disaggregated RAN ecosystems, with clear paths toward integration with RICs and broader OA-RAN testbeds.

Abstract

The rapid advancement of 5G networks and the upcoming transition to 6G necessitate the use of the Open Radio Access Network (O-RAN) architecture to enable greater flexibility, interoperability, and innovation. This shift towards 6G and O-RAN requires the development of advanced simulation tools for testing, analyzing, and optimizing Radio Access Network (RAN) operations. This need becomes critical due to the complex dynamics of mobility management inherent in the 6G vision and next-generation networks. These networks anticipate advanced handover methods for mobile users, UAVs, IoT devices, and beyond. Addressing this gap, this paper introduces RANFusion: a robust RAN simulator specifically created to explore a variety of handover scenarios and to test and balance resources between users. This tool enables precise simulations for refining handover strategies within RAN and O-RAN environments, thereby ensuring optimal performance and reliability in these advanced network infrastructures.
Paper Structure (9 sections, 5 equations, 5 figures, 2 tables)

This paper contains 9 sections, 5 equations, 5 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Handover in Next-G
  4. RANFusion: System Design and Architecture
  5. Requirement
  6. Setup Networks
  7. Components
  8. Experiment Results
  9. Future research directions

Figures (5)

  • Figure 1: Cell Sectorization Architecture
  • Figure 2: Multiple Handover Scenarios in Future Networks
  • Figure 3: Architecture of RANFusion
  • Figure 4: The command-line user interface
  • Figure 5: (a) Handover peak during the time, (b) load ratio comparison before and after load balancing, showing traffic load on sector A before and after load balancing (c).