Energy Efficient Data Rate Enhancement Channel Coding Technique for Narrowband Internet of Things (NB-IoT) - Migabo, Emmanuel; Djouani, Karim; Kurien, Anish (Proceedings (African Electrical Technology Conference), 2021)
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.