基于H-CRAN中的深度增强学习的节能动态增强型细胞间干扰协调方案
Hyungwoo Choi1, Taehwa Kim2, Seungjin Lee1
1College of AI/SW Convergence, Kyungnam University, 7 Gyeongnamdaehak-ro, Masanhappo-gu, Changwon 51767, Republic of Korea.
Sensors (Basel, Switzerland)
|January 8, 2025
概括
本研究介绍了使用深度强化学习 (DRL) 来管理干扰和节省电力的5G网络的新能源效率方法. 这项新方案显著减少了能源消耗,同时提高了异构云无线电接入网络 (H-CRAN) 的服务质量.
科学领域:
- 无线通信无线通信
- 网络工程 网络工程
- 人工智能的人工智能
背景情况:
- 5G网络提供高速和低延迟,但在异质云无线电接入网络 (H-CRAN) 中面临挑战.
- 管理细胞间干扰和节约能源是H-CRAN部署中的关键问题.
- 传统的干扰协调方法在优化能效方面存在局限性.
研究的目的:
- 为5G H-CRAN提出一种新的节能,动态增强的细胞间干扰协调 (eICIC) 方案.
- 将能源消耗和服务质量 (QoS) 整合到eICIC优化过程中.
- 提高5G网络的可持续性和性能.
主要方法:
- 开发了一个基于深度强化学习 (DRL) 的eICIC计划.
- 在几乎空白子 (TPA) 和受害者用户设备 (CTV) 的频道质量指标 (CQI) 值期间引入传输功率作为优化参数.
- 模拟的信号与干扰加噪声比率 (SINR) 和服务率来定义能源效率.
主要成果:
- 拟议的基于DRL的eICIC计划实现了显著的能源节约,高达70%.
- 该计划证明了服务质量 (QoS) 满意度的提高.
- 能源公用事业效率指标有效地平衡了节能和QoS.
结论:
- 新的eICIC计划为节能和高性能5G H-CRAN提供了一个有希望的解决方案.
- 在复杂的无线网络中,DRL是动态资源管理的有效方法.
- 这些发现有助于开发可持续和高效的未来无线通信系统.
相关概念视频
Associative Learning
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Classical conditioning, also known...
Reinforcement
Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
Reinforcement Schedules
Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
Once a behavior is learned,...


