Browsing by Author "Ammuri, Rula"

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    Achievable Rates of Full Duplex Cooperative Relay Selection-Based Machine Learning
    (IEEE, 2025) Belaoura, Widad; Althunibat, Saud; Mazen, Hasna; Qaraqe, Khalid; Ammuri, Rula
    Machine learning (ML) is an advanced artificial intelligence technology that addresses the ever-growing complexity in communication signal processing. In this paper, the concept of ML-based classification model to choose the best relay is investigate in a full duplex (FD) cooperative system. Specifically, a K-nearest neighbors (KNN)-based relay selection is applied to accurately predict and evaluate the achievable rate of the optimal FD relay. The core idea of the multi-class KNN is to identify the optimal relay that yields the highest achievable rate performance by utilizing a large set of offline training data derived from the channel state information (CSI), ensuring that no further training is required during system processing. The results indicate that the KNN-based FD relay selection can achieve an achievable rate comparable to the optimal exhaustive search method with lower computation complexity.