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Random Access Using Deep Reinforcement Learning in Dense Mobile Networks
2021
Sensors
5G and Beyond 5G mobile networks use several high-frequency spectrum bands such as the millimeter-wave (mmWave) bands to alleviate the problem of bandwidth scarcity. However high-frequency bands do not cover larger distances. The coverage problem is addressed by using a heterogeneous network which comprises numerous small and macrocells, defined by transmission and reception points (TRxPs). For such a network, random access is considered a challenging function in which users attempt to select
doi:10.3390/s21093210
pmid:34063132
fatcat:qr5uur4d3zbnriw4qg32pgg2l4