Deep Reinforcement Learning-Based Resource Allocation for mm-Wave Dense 5G Networks

被引：0
作者：
Martyna, Jerzy [1 ]
机构：
[1] Jagiellonian Univ, Inst Comp Sci, Fac Math & Comp Sci, ul Prof S Lojasiewicza 6, PL-30348 Krakow, Poland
来源：
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2022 | 2022年 / 13469卷
关键词：
D O I：
10.1007/978-3-031-15471-3_26
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In microwave technology, directional beams are used for the propagation of radio waves. Nevertheless, significant errors occur in localizing the receiver. The paper presents the method for radio resource allocation and beam management based on the double deep Q-learning algorithm. Simulation studies confirm that the proposed method significantly improves the efficiency of the millimeter 5G network.
引用
收藏
页码：298 / 307
页数：10
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