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IEEE/ICACT20260367 Slide.13        [Big Slide]	Oral Presentation
	After predicting future RU performance metrics (RB usage, throughput, and BLER) with the BiLSTM model, we formulate a linear programming–based traffic steering problem to optimally allocate UE traffic across RUs. Each UE¡¯s traffic is divided among available RUs to maximize a weighted utility that favors high throughput while penalizing BLER and excessive RB usage, subject to constraints on RU capacity, reliability, and minimum throughput requirements. The resulting optimization problem is solved using a Gurobi solver at every time slot with updated predictions, enabling real-time, prediction-aware adaptation of UE–RU assignments for improved network performance.

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