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Related Experiment Video

Updated: Jul 2, 2025

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Energy-Efficient BWP Configuration for Multi-Slice Users.

Joe Saad^1,2, Kinda Khawam², Mohamad Yassin¹

¹Orange Innovation, 44 Avenue de la République, 92320 Châtillon, France.

Sensors (Basel, Switzerland)

|February 24, 2024

Summary

This summary is machine-generated.

Fifth Generation (5G) networks use Bandwidth Parts (BWPs) for energy efficiency. This study proposes two new BWP selection methods for multi-slice users to optimize energy consumption based on battery levels.

Keywords:

5G BWP QoS energy efficiency multi-slice connectivity

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Area of Science:

Telecommunications Engineering
Wireless Network Optimization
Energy Efficiency in Mobile Networks

Background:

Fifth Generation (5G) mobile networks enable network slicing for service isolation.
User Equipment (UE) can connect to multiple slices and utilize multiple Bandwidth Parts (BWPs).
Scanning multiple BWPs is energy-intensive for multi-slice UEs.

Purpose of the Study:

To propose energy-efficient Bandwidth Part (BWP) selection solutions for multi-slice User Equipment (UE) in 5G networks.
To analyze the impact of battery level, sojourn time, and scanned BWP size on energy efficiency.
To compare centralized and distributed BWP selection approaches.

Main Methods:

Development of a centralized BWP selection approach for optimal UE configuration.
Implementation of a distributed BWP selection approach using non-cooperative game theory.
Simulation analysis comparing proposed schemes against legacy solutions.

Main Results:

Both proposed energy-efficient BWP selection solutions demonstrate significant improvements.
The schemes effectively enhance user energy efficiency while maintaining quality of service.
Performance is validated considering battery level, sojourn time, and BWP size.

Conclusions:

The proposed centralized and distributed BWP selection methods offer superior energy efficiency for multi-slice 5G users.
Energy-aware BWP configuration is crucial for sustainable mobile network operation.
The study provides valuable insights for optimizing 5G UE power consumption.