Optimal User Association Strategy for Large-Scale IoT Sensor Networks with Mobility on Cloud RANs

Area of Science:

• Computer Science
• Electrical Engineering
• Telecommunications

Background:

• Mobile users' mobility in cloud radio access networks (C-RAN) impacts base station (BS) association.
• Conventional association strategies can lead to imbalanced traffic loads and frequent handovers.

Purpose of the Study:

• To develop an optimal user association strategy for large-scale mobile Internet of Things (IoT) networks on C-RAN.
• To minimize handover overhead while ensuring balanced traffic loads across BSs.

Main Methods:

• Formulated an optimal user association scheme for load balancing.
• Revised the formulation to minimize handovers while maintaining BS load balance.
• Implemented a discrete-time network simulator for performance evaluation.

Main Results:

• The proposed strategy significantly reduces the number of handovers.
• Achieved superior load balancing compared to conventional association schemes.
• Demonstrated effectiveness in large-scale mobile IoT network simulations.

Conclusions:

• The optimal user association strategy offers a viable solution for C-RAN environments.
• Addresses key challenges of user mobility, traffic load balancing, and handover reduction.
• Provides a foundation for efficient mobile IoT network management.