As the demand for high-speed, low-latency connectivity escalates, fifth generation (5G) and emerging sixth generation (6G) networks face significant challenges in managing energy consumption while maintaining performance standards. This paper investigates the application of Reinforcement Learning (RL) for dynamic energ...
C. Katsigiannis, Konstantinos Tsachrelias, V. Kokkinos et al.· International Symposium on N...· 0 citations
Ultra-dense 5G networks require advanced traffic steering to maintain performance and balance load amid growing user and base station (gNB) densities. Traditional heuristics such as nearest-base-station and Signal-to-Interference-plus-Noise Ratio (SINR)-based selection provide simple solutions but struggle to adapt to...
Damianos Diasakos, V. Kokkinos, C. Bouras et al.· International Conference on...· 0 citations
Comparison shows that, under the evaluated DeepMIMO-based scenarios, the examined assignment-based methods exhibit different trade-offs in throughput, energy-consumption-related performance, bandwidth utilization, and adaptability to varying user demands, offering useful insights for 5G MIMO resource allocation studies...
Nikolaos Prodromos, Damianos Diasakos, V. Kokkinos et al.· Wireless personal communicat...· 0 citations
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