Interference Mitigation in 5G Networks: Review, Challenges, and Deep Learning-Based SIC Framework

Lateef Kabiru; Abdulrahman Yusuf Amuda; Jimoh Akanni; Akindele Segun Afolabi

doi:10.51173/eetj.v3i2.52

Authors

Lateef Kabiru Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria
Abdulrahman Yusuf Amuda Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria
Jimoh Akanni Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria
Akindele Segun Afolabi Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria

DOI:

https://doi.org/10.51173/eetj.v3i2.52

Keywords:

Channel Estimation, NOMA, Successive Interference Cancellation (SIC), Deep Learning (DL), Interference Mitigation

Abstract

The fifth generation (5G) network represents an advancement in mobile communication technology in a region with increasing demands in usage to solve the problem of traffic congestion, high latency, and low speed. However, interference is one of the major limiting factors that degrades the 5G network performance. The adverse effects of interference have led to several research studies into mitigation techniques for 5G networks. This paper presents a comprehensive review of interference types and mitigation techniques in 5G networks, including conventional approaches such as power control, inter-cell interference coordination, beamforming, and resource allocation. Moreover, this work provides an analytical framework for Deep Learning (DL)-Based Channel Estimation and Successive Interference Cancellation (SIC) in 5G non-orthogonal multiple access (NOMA) systems. This study extends existing models by incorporating residual interference modeling, highlighting the impact of error propagation in SIC systems. This paper synthesizes existing techniques, identifies key research gaps such as: imperfect channel estimation as in the conventional SIC, failure to address the error components caused by the residual interference that is often adhered to SIC technique, and establishes a unified perspective on integrating DL into interference mitigation, showing that DL-Based SIC has strong potential for improving interference resilience. We believe that our proposed technique will serve as guidelines for moving forward with SIC aware protocol research in 5G and Beyond 5G networks.

Author Biographies

Abdulrahman Yusuf Amuda , Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria

Electrical and Electronics Engineering Department, Professor

Jimoh Akanni, Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria

Electrical and Electronics Engineering Department, Senior Lecturer

Akindele Segun Afolabi, Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria

Electrical and Electronics Engineering Department, Senior Lecturer

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