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Hierarchical Reinforcement Learning for Relay Selection and Power Optimization in Two-Hop Cooperative Relay Network [article]

Yuanzhe Geng, Erwu Liu, Rui Wang, Yiming Liu
2021 arXiv   pre-print
In this paper, we study the outage probability minimizing problem subjected to a total transmission power constraint in a two-hop cooperative relay network.  ...  A key difference from other RL-based methods in existing literatures is that, our proposed HRL approach decomposes relay selection and power allocation into two hierarchical optimization objectives, which  ...  In this section, we propose a novel two-level HRL framework for cooperative communication, to learn relay selection policy and power allocation policy in different levels. A.  ... 
arXiv:2011.04891v2 fatcat:l5bf3emq4zh5rmgulpndztl32u

Optimization-driven Hierarchical Learning Framework for Wireless Powered Backscatter-aided Relay Communications [article]

Shimin Gong, Yuze Zou, Jing Xu, Dinh Thai Hoang, Bin Lyu, Dusit Niyato
2020 arXiv   pre-print
The optimization-driven H-DDPG algorithm firstly decomposes the binary relay mode selection into the outer-loop deep Q-network (DQN) algorithm and then optimizes the continuous beamforming and relaying  ...  In this paper, we employ multiple wireless-powered relays to assist information transmission from a multi-antenna access point to a single-antenna receiver.  ...  two-hop hybrid relaying communications.  ... 
arXiv:2008.01366v1 fatcat:g6nvvfmlizcezfgre7e2lzxdx4

2020 Index IEEE Transactions on Wireless Communications Vol. 19

2020 IEEE Transactions on Wireless Communications  
., and Saad, W., Joint Access and Backhaul Resource Management in Satellite-Drone Networks: A Competitive Market Approach; TWC June 2020 3908-3923 Hu, Y.H., see Xia, M., TWC June 2020 3769-3781 Hua,  ...  Identification for MIMO Systems in Dynamic Environments; TWC June 2020 3643-3657 Huang, C., see Yang, M., TWC Sept. 2020 5860-5874 Huang, D., Tao, X., Jiang, C., Cui, S., and Lu, J  ...  ., +, TWC March 2020 1786-1801 Joint Relay Selection and Power Allocation for Underwater Cooperative Optical Wireless Networks.  ... 
doi:10.1109/twc.2020.3044507 fatcat:ie4rwz4dgvaqbaxf3idysubc54

Reinforcement Learning Based Relay Selection for Underwater Acoustic Cooperative Networks

Yuzhi Zhang, Yue Su, Xiaohong Shen, Anyi Wang, Bin Wang, Yang Liu, Weigang Bai
2022 Remote Sensing  
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY  ...  [31] investigated reinforcement learning based joint relay selection and power allocation in energy harvesting UWA cooperative networks.  ...  [32] investigated the power allocation problem in energy harvesting full duplex UWA cooperative relay network by reinforcement learning.  ... 
doi:10.3390/rs14061417 dblp:journals/remotesensing/ZhangSSWWLB22 fatcat:4im62v3xw5babnu76vsifxgfu4

2021 Index IEEE Transactions on Green Communications and Networking Vol. 5

2021 IEEE Transactions on Green Communications and Networking  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TGCN June 2021 737-749 Multi-Agent Reinforcement Learning for Energy Harvesting Two-Hop Communications With a Partially Observable System State.  ... 
doi:10.1109/tgcn.2021.3131006 fatcat:6l377alf65ho7ab752c2v2dvve

Table of contents

2021 IEEE Wireless Communications Letters  
Mohammed Elamassie and Murat Uysal 1964 Deep Deterministic Policy Gradient for Relay Selection and Power Allocation in Cooperative Communication Network . . . . . . . . . . . . . . . . . . . . . .  ...  Blefari Melazzi 1989 Intelligent Trajectory Planning in UAV-Mounted Wireless Networks: A Quantum-Inspired Reinforcement Learning Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/lwc.2021.3105857 fatcat:nzelozqixra57l3hlzgga62pd4

Table of Contents

2022 IEEE Transactions on Communications  
Urbanke 163 Machine Learning and Communications Hierarchical Reinforcement Learning for Relay Selection and Power Optimization in Two-Hop Cooperative Relay Network .Liu 171 Construction of Polar Codes  ...  Liew, and H. Chen 404 Power Minimization for Age of Information Constrained Dynamic Control in Wireless Sensor Networks .............  ... 
doi:10.1109/tcomm.2021.3134447 fatcat:e4krnpts75a4fk23jcmielpv4m

Reinforcement Learning Based Robust Policy Design for Relay and Power Optimization in DF Relaying Networks [article]

Yuanzhe Geng, Erwu Liu, Rui Wang, Pengcheng Sun, Binyu Lu
2022 arXiv   pre-print
RL method is to learn from the interaction with communication environment, optimize its action policy, and then propose relay selection and power allocation schemes.  ...  In this paper, we study the outage minimization problem in a decode-and-forward cooperative network with relay uncertainty.  ...  In [18] , [19] , the authors divided relay selection and power optimization into two sub-problems and then solved them through hierarchical RL architecture, in order to maximize total SNR and minimize  ... 
arXiv:2205.09106v1 fatcat:scofxwr6gngynhfjuu7gpbhdpu

2013 Index

2014 IEEE Transactions on Wireless Communications  
-that appeared in this periodical during 2013, and items from previous years that were commented upon or corrected in 2013.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Zhang, Shun, +, TWC March 2013 1300-1309 Source Power Allocation and Relaying Design for Two-Hop Interference Networks with Relay Conferencing.  ... 
doi:10.1109/twc.2011.09.499-tw1401-index fatcat:w5ya5mg3sbcodb2crtuaoyk3su

Survey on Recent Advancements in Energy-Efficient Routing Protocols for Underwater Wireless Sensor Networks

Shreya Khisa, Sangman Moh
2021 IEEE Access  
Underwater wireless sensor networks (UWSNs) have become highly efficient in conducting various operations in maritime environments.  ...  Compared to terrestrial wireless sensor networks, routing protocols in UWSNs are prone to high propagation delay, high energy consumption, low bandwidth, and low throughput.  ...  ACKNOWLEDGMENT The authors thank the editor and the anonymous referees for their comments that have helped improve the quality of this paper.  ... 
doi:10.1109/access.2021.3071490 fatcat:pv4425d4mjh2vaim7l5wn2qsuu

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
Kim, D.I., Mechanism Design for Wireless Powered Spatial Crowdsourcing Networks; TVT Jan. 2020 920-934 Jibrin, R., see Jia, Y., TVT Dec. 2020 14173-14187 Jin, B., see Zhu, Y., TVT Aug. 2020 8317-8328  ...  Revocable Data-Sharing Scheme in VANETs; TVT Dec. 2020 15933-15946 Hoseini, S.A., Ding, M., Hassan, M., and Chen, Y., Analyzing the Impact of Molecular Re-Radiation on the MIMO Capacity in High-Frequency  ...  Adaptive Relay Selection Strategies for Cooperative NOMA Networks With User and Relay Cooperation.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

An Energy-efficient Distributed Adaptive Cooperative Routing Based on Reinforcement Learning in Wireless Multimedia Sensor Networks

Denghui Wang, Jian Liu, Dezhong Yao
2020 Computer Networks  
Complex task processing and frequent data communication in Wireless Multimedia Sensor Networks (WMSN) demand for energy-efficient and Quality of Service (QoS) guarantee to support new applications especially  ...  Particularly, we design a reinforcement learning based mechanism to perform QoS and energy balanced routing according to the knowledge of reliability and delay.  ...  It is difficult for each hop on the cooperative routing path to determine whether to relay transmission and select the optimal one among the relay nodes set.  ... 
doi:10.1016/j.comnet.2020.107313 fatcat:dqijww4pjbegndokxjt2r26fse

An Overview of Machine Learning-Based Energy-Efficient Routing Algorithms in Wireless Sensor Networks

Qianao Ding, Rongbo Zhu, Hao Liu, Maode Ma
2021 Electronics  
Traditional green routing algorithms aim to achieve this by reducing energy consumption and prolonging network lifetime through optimized routing schemes in WSNs.  ...  In this paper, we survey and propose a theoretical hypothetic model formulation of ML as an effective method for creating a power-efficient green routing model that can overcome the limitations of traditional  ...  Based on reinforcement learning, two centralized and distributed routing schemes were designed and implemented in WSNs [72] .  ... 
doi:10.3390/electronics10131539 fatcat:ak4i26hwa5hbflxngv7tk2s2e4

Relaying in the Internet of Things (IoT): A Survey

Uyoata Uyoata, Joyce Mwangama, Ramoni Adeogun
2021 IEEE Access  
In [59] , the authors present a search method for obtaining the optimal relay selection and power allocation for relays assisting sky cameras in an energy harvesting wireless sensor network.  ...  Tree SVM Support Vector Machine RL Reinforcement Learning RS Relay Selection AS Antenna Selection PHS Physical Layer Security CAR Cache-Aided Relaying AC Access Control PA Power Allocation  ... 
doi:10.1109/access.2021.3112940 fatcat:beo5j6hyd5hwhlxj4mp5vok4sq

A Multi-Agent Framework for Packet Routing in Wireless Sensor Networks

Dayong Ye, Minjie Zhang, Yun Yang
2015 Sensors  
Such cooperative neighbours, in turn, can help the sensor to effectively relay packets in the future.  ...  Wireless sensor networks (WSNs) have been widely investigated in recent years.  ...  Madeleine Strong Cincotta, who provided professional language editing for us. Author Contributions Dayong Ye and Minjie Zhang created the major part of this paper.  ... 
doi:10.3390/s150510026 pmid:25928063 pmcid:PMC4481995 fatcat:2pnom3mj35cmhbhzsofp5e4fuq
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