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Prediction-Based Energy Saving Mechanism in 3GPP NB-IoT Networks
1School of Electrical and Electronics Engineering, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea. jinseong.lee@yonsei.ac.kr.
Sensors (Basel, Switzerland)
|September 2, 2017
Summary
This study introduces a prediction-based energy saving mechanism (PBESM) for Narrowband IoT (NB-IoT) devices. The PBESM reduces energy consumption by up to 34%, extending device lifespan through optimized uplink transmissions.
Area of Science:
- Telecommunications Engineering
- Wireless Communication Systems
- Internet of Things (IoT)
Background:
- The expansion of the Internet of Things (IoT) necessitates communication platforms with wide coverage and low energy consumption.
- Narrowband IoT (NB-IoT), standardized by the 3rd Generation Partnership Project, aims to provide long-lasting IoT devices (over 10 years) without battery replacement.
- Significant energy is consumed by the power amplifier during radio transmission, making uplink transmission time reduction critical for device longevity.
Purpose of the Study:
- To propose a novel prediction-based energy saving mechanism (PBESM) to reduce energy consumption in NB-IoT devices.
- To enhance uplink transmission efficiency by minimizing random accesses and optimizing radio resource allocation.
- To extend the operational lifespan of NB-IoT devices by reducing power demands.
Main Methods:
- The proposed PBESM incorporates a network architecture utilizing deep packet inspection to predict uplink packet occurrences.
- An algorithm is developed to predict processing delays and proactively assign radio resources, improving the scheduling request procedure.
- The mechanism focuses on reducing the number of random accesses required for uplink transmissions.
Main Results:
- Simulations demonstrate a significant reduction in energy consumption compared to conventional NB-IoT methods.
- The proposed PBESM achieved up to a 34% reduction in energy consumption.
- The enhanced scheduling request procedure and reduced random accesses contribute to overall energy savings.
Conclusions:
- The prediction-based energy saving mechanism (PBESM) effectively reduces energy consumption in NB-IoT uplink transmissions.
- PBESM enhances NB-IoT device longevity by minimizing power usage, crucial for widespread IoT deployment.
- The proposed approach offers a viable solution for improving the energy efficiency of low-power wide-area networks.
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