# Interference Mitigation Strategies in Beyond 5G Wireless Systems: A Review
## 4 Interference Mitigation Schemes and Techniques by 3 GPP
### Interference Management for NTN and 6G Emerging Architectures  
As B5G networks continue to evolve, the integration of NTNs and the anticipated shift toward 6G AI-native architecture bring new challenges and opportunities for IM. 3 GPP Releases 17 and 18 have initiated formal study items on new radio for satellite access and interworking between terrestrial and non-terrestrial components. In such deployments, interference arises from beam overlaps, Doppler shifts, and asynchronous transmissions between ground terminals and moving satellite platforms [179; 221]. Effective IM solutions must consider PS, adaptive BF, and cross-layer coordination that accounts for orbital dynamics and propagation delays.  
In parallel, AI-native networks envisioned in 6G will require fully automated IM mechanisms. These will rely on distributed intelligence embedded in the RAN and core to support RT IPR, mitigation, and resource orchestration [222]. Unlike conventional model-driven techniques, 6G IM frameworks are expected to use continual learning, self-evolving  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Technique** & **Urban Dense** & **Rural** & **UAV/NTN** & **Infrastructure-Limited** \\ \hline CoMP & ✓ & ✗ & — & ✗ \\ eICIC & ✓ & — & ✗ & ✓ \\ POC & — & ✓ & — & ✓ \\ AI-Based & ✓ & — & ✓ & — \\ \hline \end{tabular}
\end{table}
Table 10: Suitability of various IMI techniques across different B5G deployment scenarios. Check marks (✓) indicate strong suitability, dashes (—) represent moderate feasibility with limitations, and crosses (✕) denote low practical viability.  
Figure 10: Comparative evaluation of IMI techniques based on five performance metrics: scalability, real-world applicability, implementation complexity, CO, and SE.  
policies, and federated intelligence to adapt across highly dynamic, heterogeneous environments. These solutions will need to address multi-dimensional interference, including from aerial devices, IoT swarms, and multi-access edge nodes without centralized control.  
Moreover, the convergence of communication and sensing, often referred to as integrated sensing and communication (ISAC), will add new complexity to interference modeling. In ISAC systems, signals used for data transmission also carry radar or positioning functions, which can interfere with coexisting transmissions unless tightly coordinated. Emerging 3 GPP and international telecommunication union discussions on 6G recognize the need for spectrum-aware waveform design and dual-function resource scheduling to manage this new interference class [223, 224]. Recent studies also explore AI-based IMI in ISAC systems, which enable intelligent coordination between sensing and communication tasks in dense, dynamic environments [225].  
Together, these trends underscore the necessity for IM strategies that are not only adaptive and intelligent but also cross-domain, spanning terrestrial, aerial, and orbital layers. Advancing these solutions will be key to realizing the low-latency, high-reliability, and massive-connectivity goals of 6G.