Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System With Online Reinforcement Learning

Nguyen Van Huynh; Dinh Thai Hoang; Diep N. Nguyen; Eryk Dutkiewicz; Dusit Niyato; Ping Wang

首页> 外文期刊>IEEE Transactions on Communications >Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System With Online Reinforcement Learning

【24h】

Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System With Online Reinforcement Learning

机译：具有在线增强学习功能的射频供电环境后向散射系统的最佳且低复杂度的动态频谱访问

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Ambient backscatter has been introduced with a wide range of applications for low power wireless communications. In this paper, we propose an optimal and low-complexity dynamic spectrum access framework for the RF-powered ambient backscatter system. In th

机译：环境背向散射已被引入到低功率无线通信的广泛应用中。在本文中，我们为射频供电的环境反向散射系统提出了一种最佳且低复杂度的动态频谱接入框架。在

著录项

来源
《IEEE Transactions on Communications》 |2019年第8期|5736-5752|共17页
作者
Nguyen Van Huynh; Dinh Thai Hoang; Diep N. Nguyen; Eryk Dutkiewicz; Dusit Niyato; Ping Wang;
展开▼
作者单位

School of Electrical and Data Engineering University of Technology Sydney Sydney NSW Australia;

School of Electrical and Data Engineering University of;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词
Backscatter; Heuristic algorithms; Receivers; Throughput; Optimization; Radio frequency; Energy harvesting;

机译：反向散射;启发式算法;接收器;吞吐量;优化;无线电频率;能量收集;

相似文献

外文文献
中文文献
专利

1. Optimal decision making in multi-channel RF-powered cognitive radio networks with ambient backscatter capability [J] . Zakariya Ahmed Y., Rabia Sherif I., Zahra W. K. Computer networks . 2021,第Apra22期

机译：具有环境反向散射能力的多通道RF动力认知无线网络的最佳决策
2. Optimal Resource Allocation for RF-Powered Underlay Cognitive Radio Networks With Ambient Backscatter Communication [J] . Yuandong Zhuang, Xi Li, Hong Ji, IEEE Transactions on Vehicular Technology . 2020,第12期

机译：具有环境反向散射通信的RF供电底层认知无线电网络的最优资源分配
3. Dynamic Access Point and Service Selection in Backscatter-Assisted RF-Powered Cognitive Networks [J] . Gao Xiaozheng, Feng Shaohan, Niyato Dusit, Internet of Things Journal, IEEE . 2019,第5期

机译：反向散射辅助射频供电的认知网络中的动态接入点和服务选择
4. Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter [C] . Nguyen Van Huynh, Dinh Thai Hoang, Diep N. Nguyen, IEEE Global Communications Conference . 2019

机译：具有环境反向散射的RF动力认知无线电网络的加固学习方法
5. Explaining Collective Behavior with Dynamical Systems: Spatial Gradient Sensing in Eukaryotic Chemotaxis and Learning Dynamics in Multiagent Reinforcement Learning [D] . Shams, Daniel . 2019

机译：用动力系统解释集体行为：多核化趋化性的空间梯度传感和多核强化学习中的学习动态
6. A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks [O] . Yun Lin, Chao Wang, Jiaxing Wang, 2016

机译：基于增强学习的认知无线电传感器网络动态频谱接入框架
7. Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter [O] . Nguyen Van Huynh, Dinh Thai Hoang, Diep N. Nguyen, 2018

机译：具有环境反向散射的RF动力认知无线电网络的加固学习方法
8. Optimal Myopic Sensing and Dynamic Spectrum Access in Centralized Secondary Cognitive Radio Networks with Low-complexity Implementations. [R] . Li, Y., Jayaweera, S. K., Bkassiny, M., 2011

机译：低复杂度实现的集中式次级认知无线电网络中的最佳近视感知和动态频谱接入。

Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System With Online Reinforcement Learning

摘要

著录项

相似文献

相关主题

期刊订阅