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Recent Advances on Cellular D2D Communications

Boon-Chong Seet, Syed Hasan, Peter Chong
2018 Future Internet  
Elias Yaacoub provided useful suggestions based on to improve the system model and basic components of the method.  ...  The authors thank Dario Di Giacomo for his work to optimize the algorithm. Author Contributions: All the authors contributed equally to the paper. R.  ...  We apply a Reinforcement learning (RL) algorithm named state action reward state action, SARSA(λ), for adaptive resource in D2D communication for efficient resource allocation.  ... 
doi:10.3390/fi10010010 fatcat:hizax5tiazegjovg6p2z3ywt2y

Book Reviews

2020 IEEE wireless communications  
A deep reinforcement learning algorithm has been used to design an autonomous self-organizing path planning mechanism for UAV UEs.  ...  for IoT and communications.  ... 
doi:10.1109/mwc.2020.9241877 fatcat:h7sr5ge5d5f7rdxvgxcsjlsj3q

Table of contents

2021 IEEE Communications Letters  
Kot 2609 Deep Reinforcement Learning-Based Dynamic Spectrum Access for D2D Communication Underlay Cellular Networks .................................................................... J. Huang, Y.  ...  Liu 2614 Learning Driven Resource Allocation and SIC Ordering in EH Relay Aided NB-IoT Networks ......................... ...........................................................................  ... 
doi:10.1109/lcomm.2021.3097423 fatcat:4zve3vaudrctfh5cagr5pioufi

Table of Contents

2020 IEEE Transactions on Vehicular Technology  
Yang 2878 A New Block-Based Reinforcement Learning Approach for Distributed Resource Allocation in Clustered IoT Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Han 3190 Efficient Resource Allocation and Power Control for LTE-A D2D Communication With Pure D2D Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tvt.2020.2970959 fatcat:rmi2juemdneozo47iagkyagi6i

IEEE TCCN Special Section Editorial: Evolution of Cognitive Radio to AI-Enabled Radio and Networks

Yue Gao, Ekram Hossain, Geoffrey Ye Li, Kevin Sowerby, Carlo Regazzoni, Lin Zhang
2020 IEEE Transactions on Cognitive Communications and Networking  
The In the twelfth article, entitled "Learning-Based Spatial Reuse for WLANs With Early Identification of Interfering Transmitters", by Yin et al., a reinforcement learningbased spatial reuse scheme for  ...  Finally, the last article, "Market-Based Model in CR-IoT: A Q-Probabilistic Multi-agent Reinforcement Learning Approach", by Wang et al., proposes a multi-agent reinforcement learning (MARL) algorithm  ... 
doi:10.1109/tccn.2020.2975440 fatcat:lofvpltbibcwvnpfqaivkh7eyq

First 20 Years of Green Radios [article]

Shunqing Zhang and Shugong Xu and Geoffrey Ye Li and Ender Ayanoglu
2019 arXiv   pre-print
By introducing green radio schemes for advanced terminals and future wireless networks, this article will not only be beneficial for readers with only preliminary background in communications and signal  ...  processing but also have reference and historical values for researchers and practical engineers in the area.  ...  To provide more accurate decision making for energy efficient applications, reinforcement learning has been widely used for energy harvesting related problems, such as in [99] .  ... 
arXiv:1908.07696v1 fatcat:dbjg4rykl5eyjjvia55sjxo6xa

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
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 Jin, D., see  ...  see Gholami, R., TVT Sept. 2020 9938-9950 Hoki, K., see Kawakami, T., TVT Dec. 2020 16168-16172 Hong, C., Shan, H., Song, M., Zhuang, W., Xiang, Z., Wu, Y., and Yu, X., A Joint Design of Platoon Communication  ...  ., +, TVT Jan. 2020 4-15 A New Block-Based Reinforcement Learning Approach for Distributed Resource Allocation in Clustered IoT Networks.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

2020 Index IEEE Transactions on Mobile Computing Vol. 19

2021 IEEE Transactions on Mobile Computing  
., +, TMC Nov. 2020 2489-2504 Distributed Learning in Noisy-Potential Games for Resource Allocation in D2D Networks.  ...  ., +, TMC May 2020 1072-1083 Distributed Learning in Noisy-Potential Games for Resource Allocation in D2D Networks.  ... 
doi:10.1109/tmc.2020.3036773 fatcat:6puiux5lp5bfvjo47ey7ycwyfu

2021 Index IEEE Transactions on Wireless Communications Vol. 20

2021 IEEE Transactions on Wireless Communications  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  mmWave Communication Signals: A Subspace Energy-Efficient Mode Selection and Resource Allocation for D2D-Enabled Heterogeneous Networks: A Deep Reinforcement Learning Approach.  ...  ., +, TWC Feb. 2021 1065-1075 Resource Allocation in Uplink NOMA-IoT Networks: A Reinforce-ment-Learning Approach.  ... 
doi:10.1109/twc.2021.3135649 fatcat:bgd3vzb7pbee7jp75dnbucihmq

2020 Index IEEE Transactions on Wireless Communications Vol. 19

2020 IEEE Transactions on Wireless Communications  
., TWC Jan. 2020 650-664 Huang, A., see He, H., TWC Dec. 2020 7881-7896 Huang, C., Molisch, A.F., He, R., Wang, R., Tang, P., Ai, B., and Zhong, Z., Machine Learning-Enabled LOS/NLOS 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  ...  Coordinated Resource Allocation-Based Integrated Visible Light Communication and Positioning Systems for Indoor IoT.  ... 
doi:10.1109/twc.2020.3044507 fatcat:ie4rwz4dgvaqbaxf3idysubc54

2021 Index IEEE Internet of Things Journal Vol. 8

2021 IEEE Internet of Things Journal  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, JIoT May 1, 2021 7649-7660 Deep-Reinforcement-Learning-Based Proportional Fair Scheduling Control Scheme for Underlay D2D Communication.  ...  ., +, JIoT Nov. 1, 2021 16153-16164 Deep-Reinforcement-Learning-Based Proportional Fair Scheduling Control Scheme for Underlay D2D Communication.  ... 
doi:10.1109/jiot.2022.3141840 fatcat:42a2qzt4jnbwxihxp6rzosha3y

Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks

Sherief Hashima, Basem M. ElHalawany, Kohei Hatano, Kaishun Wu, Ehab Mahmoud Mohamed
2021 Electronics  
Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks.  ...  This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.  ...  A complete automatic power allocation method for Internet of things (IoT)-D2D communication based on DL are proposed in [22] .  ... 
doi:10.3390/electronics10020169 fatcat:2l764bczknhf7ctlmbsyllllme

A Review on Green Caching Strategies for Next Generation Communication Networks

M. Ishtiaque A. Zahed, Iftekhar Ahmad, Daryoush Habibi, Quoc Viet Phung, Md Munjure Mowla, Muhammad Waqas
2020 IEEE Access  
A deep reinforcement learning (DRL) method also analyzed C-RAN mode and D2D mode for user device communication in [150] .  ...  In [203] , the authors also explored MG and reinforcement learning.  ... 
doi:10.1109/access.2020.3040958 fatcat:stj6zehnh5a3jcznqckmwwtwbe

2020 Index IEEE Internet of Things Journal Vol. 7

2020 IEEE Internet of Things Journal  
., Rateless-Code-Based Secure Cooperative Transmission Scheme for Industrial IoT; JIoT July 2020 6550-6565 Jamalipour, A., see Murali, S., JIoT Jan. 2020 379-388 James, L.A., see Wanasinghe, T.R.,  ...  ., +, JIoT Aug. 2020 7234-7249 Resource Allocation for D2D-Based V2X Communication With Imperfect CSI.  ...  ., +, JIoT Aug. 2020 7234-7249 Resource Allocation for D2D-Based V2X Communication With Imperfect CSI.  ... 
doi:10.1109/jiot.2020.3046055 fatcat:wpyblbhkrbcyxpnajhiz5pj74a

Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

Saeed H. Alsamhi, Faris A. Almalki, Hatem Al-Dois, Soufiene Ben Othman, Jahan Hassan, Ammar Hawbani, Radyah Sahal, Brian Lee, Hager Saleh, Ahmed Mostafa Khalil
2021 Computational Intelligence and Neuroscience  
For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works.  ...  Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications.  ...  IoT device identification was based on data gathered from heterogeneous devices set and network traffic communication.  ... 
doi:10.1155/2021/6805151 pmid:34589123 pmcid:PMC8476267 fatcat:2rl2s6qkxbcabpwpjwcac4z6oe
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