This chapter presents an in-depth performance evaluation of multi-tier HCNs comprising MBSs and PBSs, leveraging NOMA to enhance spectral efficiency and support higher data rates anticipated in 6G wireless communication systems. These networks are particularly relevant for emerging smart environments, including smart homes, smart grids, and industrial Internet of Things (IIoT) applications, where reliable connectivity and low-latency communication are critical. However, such practical deployments often encounter severe electromagnetic disturbances, particularly impulsive noise (ImN), which arises from switching devices, electric machinery, or other transient sources. These non-Gaussian noise characteristics significantly deviate from conventional additive white Gaussian noise (AWGN) assumptions, making traditional performance analyses insufficient. To address this, the chapter utilizes a stochastic geometry-based analytical framework to evaluate and compare the performance of NOMA-enabled HCNs under both AWGN and impulsive noise environments. This comprehensive comparison includes OMA as a benchmark, examining both schemes across various noise conditions. Performance is rigorously assessed using key metrics such as outage probability, system throughput, and energy efficiency, providing insights into the robustness of each access scheme under realistic interference scenarios. The findings demonstrate that NOMA consistently outperforms OMA, even under the harsh influence of impulsive noise. Notably, the analysis identifies specific SNR regimes where NOMA exhibits the most significant performance advantages in both AWGN and ImN conditions. These insights underline the practical applicability and resilience of NOMA in future smart and industrial communication environments, establishing it as a strong candidate for deployment in noise-prone 6G networks.