학술논문

Energy Efficient Data Rate Enhancement Channel Coding Technique for Narrowband Internet of Things (NB-IoT)
Document Type
Conference
Source
2021 IEEE AFRICON AFRICON, 2021 IEEE. :1-6 Sep, 2021
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Phase shift keying
Spatial diversity
Energy efficiency
Real-time systems
Internet of Things
Time factors
Channel coding
Adaptive
data rates
Link Adaptation
Modulation Coding Scheme (MCS)
Narrowband IoT (NB-IoT)
Repetition number
Throughput
Language
ISSN
2153-0033
Abstract
The Narrowband Internet of Things (NB-IoT) has gained significant attention in the areas of real-time critical IoT applications such as industrial control. This comes with more demand in terms of the NB-IoT data rate performance. The NB-IoT data rate can be enhanced at various levels among which its modulation type, its channel coding design and even its wireless radio antenna diversity. According to the 3GPP NB-IoT standard, the NB-IoT, in its current standardized state, is limited to only handle up to the QPSK modulation. This, in terms of the modulation perspective, limits its data rate enhancement ability to respond to the growing demand of time-critical applications. Several research works have proposed an enhanced version of the NB-IoT approaches such as the spectral efficient frequency division multiplexing (SEFDM) which uses higher modulation formats. However, most of these techniques remain energy expensive. This paper proposes a 2-D channel-aware adaptive selection of the Modulation coding scheme and the transmission repetition number capable to enhance the overall data rate performance of the network while maintaining its energy efficiency. The proposed approach is simulated using the PHY layer of the MATLAB LTE toolbox. The obtained results show that as more NB-IoT nodes join the network, the proposed approach outperforms the SEFDM and the traditional fixed MCS and repetition number selection schemes, in terms of its data rate and energy efficiency.