## 4 The Proposed Adaptive Channel Coding Technique
### The Outer Loop Link Adaptation Approach
For example, given a total of 800 NB-IoT nodes considered within a cell, the proposed EEACC approach consumes 44.01% less energy compared to the NBLA approach and a 49.51% even less energy compared to the traditional repetition approach. Additionally, the behavior of the BLER performance is considered as the number of repeated transmissions was increased. This performance evaluation was aimed at assessing the impact of increasing the transmission repetition on the transmission reliability of the NB-IoT network. Therefore, the transmission power was kept constant at \(0.1\) W which translates in a constant \(SNR=-10\) dB assuming that the channel conditions did not change significantly during a particular simulation period. The obtained results are given in Figure 6.

As seen in Figure 6, the BLER is almost half of what it was for an SNR of \(-10\) dB as depicted in Figure 4 as the transmission repetition number is doubled (\(N=2\)). This translates to the fact that for doubling the number of transmission repetitions, the probability of failed block transmission is almost

Figure 4: Uplink BLER Performance Comparison as Power is varied. reduced by half. It can also be noticed that as the number of transmission repetitions increases. It is also observed that the BLER is reduced for all three approaches. It is important to notice that the BLER of the traditional repetition approach as well as the one of the NBLA approach remains close to each other as the number of transmission repetitions is increased. On the other hand, it is observed that in the case of the EEACC approach, it significantly reduces to as low as 0.18% as the repetition number \(N\) reaches the preset maximum value \(N_{Max}=10\). Figure 5: Uplink Average Energy consumption variation with increased scalability. Figure 6: Uplink BLER Performance Behaviour with increased transmission repetition number. Finally, the average transmission delay on a link basis was also evaluated as the number of NB-IoT nodes was scaled up within a cell. This is to assess the impact of network scalability on the latency performance of the NB-IoT network for the proposed EEACC approach as mechanism to evaluate the applicability of the proposed EEACC method in real-time IoT applications where low latency performance is critical. The obtained results are shown in the following figure. As it can be noticed in Figure 7, despite its increased computational activities, when compared to the NBLA and the traditional repetition approaches, the EEACC still achieves lower latency on a link basis. This is mainly due to the advancement of nowadays processors, computational energy but also time is not significant as compared to the propagation delay in a wireless network of object nodes such as sensor nodes, etc. Once again, as it can be noticed the latency performance of the NBLA and the traditional repetition approaches are quite close despite the fact the NBLA still performs with less latency as compared to the traditional repetition approach. ## 6 Conclusions

A new proposed 2-D adaptive channel coding and link adaptation technique is presented in this manuscript which is relevant to reducing the energy consumption of NB-IoT systems in lights with the current massive, time-critical, and industry ultra-reliable requirements of IoT applications. Part of this work has been accomplished through extended bibliography search and reviewing on the NB-IoT channel coding and link adaptation schemes with, each time, a brief analysis of the advantages and disadvantages of each. The proposed EEACC approach is then step-by-step developed and presented. The obtained results and their discussion clearly highlights the major contributions of the proposed approach as they clearly demonstrate a much more resilience of the proposed approach to channel impairments, resulting in enhancing the network reliability performance.