An optimization NPUSCH uplink scheduling approach for NB-IoT application via the feasible combinations of link adaptation, Resource assignment and energy efficiency

Low -power wide area (LPWA) technology, specifically Narrowband Internet of Things (NB-IoT), has emerged as a pivotal sixth -generation (6G) network technology, catering to the demands of massive -type communications (m- MTC), extended battery life, wide range coverage, and high reliability. Despite its advancements, existing studies often fall short in simultaneously addressing energy efficiency, latency, link adaptation, and resource allocation in the bandwidth -constrained environments typical of NB-IoT. The complexity of finding a comprehensive optimal solution for resource allocation is compounded by its non -convex and NP -hard combinatorial nature. This research addresses these challenges by introducing a Hybrid -Optimizer approach, which integrates link adaptation, resource allocation, and scheduling algorithms. This approach aims to identify the optimal feasible combination for each device (UE), focusing on energy conservation and improved signal reception. Applied to the Narrow Physical Uplink Shared Channel (NPUSCH) uplink scheduling in NB-IoT, this method is benchmarked against the conventional Round -Robin scheduling algorithm. Simulation results demonstrate that the HybridOptimizer approach significantly outperforms the Round -Robin algorithm in terms of scheduling processing time and energy efficiency. Furthermore, the proposed algorithm is capable of generating candidate combinations that enhance signal reception in UEs and meet the required subframe criteria, adhering to system modeling assumptions for scheduling optimization.