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Proposed Explainable Interference Control Technique in 6G Networks Using Large Language Models (LLMs)

Title: Proposed Explainable Interference Control Technique in 6G Networks Using Large Language Models (LLMs)
Authors: H. Ahmed Tahir; Walaa Alayed; Waqar Ul Hassan; Amir Haider
Source: Electronics ; Volume 13 ; Issue 22 ; Pages: 4375
Publisher Information: Multidisciplinary Digital Publishing Institute
Publication Year: 2024
Collection: MDPI Open Access Publishing
Subject Terms: AI/ML; LLM; intelligent communication; beyond 5G; 6G
Description: After the advent of 5th generation (5G) and 6th generation (6G) cellular networks, the complexity of managing real-time signal interference has increased in dense and dynamic environments. Traditional interference techniques, such as frequency reuse and allocation, while effective, lack robust adaptability and transparency needed to reduce interference in advanced communication networks. This paper introduces a novel approach that fuses large language models (LLMs) and Explainable Artificial Intelligence (XAI) to mitigate interference and enhance interference management in the mathematical foundations of 6G networks. The proposed approach provides accurate interference predictions, which the LLM balances with its complex architecture, necessary to meet the demands of beyond 5G and 6G networks, along with interpretable explanations to ensure transparency in decision-making. The proposed framework has been evaluated across various performance metrics. Interference latency consistently achieves lower rates of 0.95 s, compared to traditional techniques, which average around 1 s. Furthermore, the confidence score of the LLM shows a stable value of 0.87 throughout the system, compared to 0.85 in techniques without LLMs. Overall, the XAI-driven LLM demonstrates the potential of incorporating LLMs and XAI into wireless networks to improve resilience in next-generation networks. This proof of concept introduces a novel framework that offers new dimensions in wireless communication, particularly for interference management, prediction, and mitigation.
Document Type: text
File Description: application/pdf
Language: English
Relation: Microwave and Wireless Communications; https://dx.doi.org/10.3390/electronics13224375
DOI: 10.3390/electronics13224375
Availability: https://doi.org/10.3390/electronics13224375
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.E1EDF0F2
Database: BASE