## 1 Introduction  
Low Power Area Networks (LPWANs) are a promising technology of the Internet of Things (IoT) for future wireless communications. In the recent decade, LPWANs have rapidly developed and have been catching significant attention from many researchers around the globe. The authors in [1] identified the Narrowband Internet of Things (NB-IoT) as well as the Long Range (LoRa) as the two leading LPWAN technologies towards enabling the future of the Internet of Things within the licensed and the unlicensed bands respectively. However, more and more network performance issues are observed as the number of connected IoT devices grows rapidly in the past few years. One of such issues is the energy consumption of the network which is directly related to the network's lifetime as identified in [2]. Narrowband Internet of Things (NB-IoT) is a new narrowband radio technology introduced in the Third Generation Partnership Project release 13 for providing low-power wide-area IoT [3]. Several techniques that consider the performance enhancement of NB-IoT wireless communication systems are being studied in current research. Specifically, the authors in [4] presented a systematic review of IoT which includes different definitions, key technologies, open issues and major challenges. Furthermore, the authors in [5] provided a systematic survey regarding NB-IoT in industry. Extensive research, key enabling technologies, major NB-IoT applications of IoT in industry, and identified research trends and challenges were reviewed. At a plenary meeting in South Korea, the Third Generation Partnership Project (3 GPP) completed the standardization of NB-IoT in which NB-IoT was regarded as an important technology and a large step for 5G IoT evolution. Major telecommunication companies, including Ericsson, Nokia, and Huawei, have shown great interest in NB-IoT as part of 5G systems and have focused significant effort towards standardization. In 3 GPP standardization, repeating transmission data and the associated control signaling several times has been utilized as a base solution to achieve coverage enhancement for NB-IoT [6]. However, repeated transmissions come with a multiplicative energy cost as it has been demonstrated by several wireless networks energy consumption modeling studies such as [7; 8] which showed that the major contributors to the overall average energy consumption of a wireless network are the energy consumed during transmission as well as the energy consumed during reception. This can be represented as  
\[E_{Trans}=\frac{(P_{Tx}+P_{Rx})\times M}{B\times P_{st}} \tag{1}\]  
where  
* \(E_{trans}\) is the energy consumed by the transceiver circuit on single wireless link,
* \(P_{Tx}\) is the transmission power,
* \(P_{Rx}\) is the reception power,
* \(M\) is the uplink packet size in bits,
* \(B\) is the transmission bit rate, and
* \(P_{st}\) is the probability of successful transmission. Other previous research work such as [9] have highlighted that the use of NB-IoT link adaptation technique with adaptive modulation and coding schemes as well as adaptive power, in the context of the Long Term Evolution (LTE) would be beneficial to reduce the overall power consumption of the network. This approach however, is limited to the context of using the QPSK modulation scheme to ensure low complexity. Other approaches such as [10; 11] propose the use of a scheduler for the NB-IoT system as a mechanism to enhance its overall average delay, to ensure efficient energy and other resources usage and to reduce nodes' processing time. Finally, authors in [12] propose the repeated transmission approach coupled with efficient bandwidth allocation as a mechanism to achieve energy efficiency. This article seeks to mitigate the high energy consumption by proposing an adaptive energy-efficient channel coding approach.