Cognitive radio-assisted optimization of NB-IoT networks under massive device density

The rapid expansion of the Internet of Things (IoT) and the deployment of 5G and beyond networks have led to massive device connectivity, creating major challenges for Low-Power Wide-Area Network (LPWAN) technologies such as Narrowband Internet of Things (NB-IoT). In particular, NB-IoT networks suffer from spectrum congestion and Quality of Service (QoS) degradation due to limited narrowband channels, rigid licensed spectrum allocation, and increasing traffic demand under high device density. This work proposes a cognitive NB-IoT framework that integrates cognitive-radio capability with priority-aware device reconfiguration to improve spectrum utilization and service reliability. An SDR-based sensing module deployed near the base station (BS) continuously monitors a wideband spectrum and identifies candidate channels. The resulting spectrum information is fed back to the BS to support dynamic spectrum-aware decisions. To mitigate congestion, the BS maintains a device-level database containing transmission parameters, repetition factors, and application priorities. When active devices exceed cell capacity, two complementary reconfiguration strategies are employed. First, devices imposing high resource demand are selectively migrated to alternative channels to alleviate congestion. Second, a priority-aware mechanism ensures that mission-critical services such as healthcare and smart grid applications are preserved on the primary NB-IoT carrier, while eligible lower-priority devices are dynamically redirected to auxiliary bands. Simulation results across the evaluated scenarios demonstrate that the proposed CRANE-NB framework significantly improves network performance. In particular, under the resource-scarcity scenario (Scenario 2), Strategy 2 achieves up to 65% reduction in average waiting time, 75% reduction in packet loss probability, and more than 77% reduction in per-packet energy consumption compared with conventional NB-IoT operation.