Advanced AI techniques for optimizing resource allocation in 6G ...
The advancement of 6G networks necessitates efficient resource allocation to maintain optimal Quality of Service (QoS) across dynamically managed network slices. Traditional centralized approaches to network resource allocation pose significant scalability, privacy, and computational bottlenecks. This study introduces a Federated Learning -based Dynamic Resource Allocation Model (FL-DRAM) that ...
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Optimizing 6G Network Slicing with the EvoNetSlice Model for Dynamic Resource Allocation and Real-Time QoS Management. International Research Journal of Multidisciplinary Technovation, 6(3), 325-340.
Machine Learning for Large
In this paper, we systematically review the most representative " learning to optimize" techniques in diverse domains of 6G wireless networks by identifying the inherent feature of the underlying optimization problem and investigating the specifically designed ML frameworks from the perspective of optimization.
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