Chun-mei Chen, He-song Jiang, Bin Wu, Hong Jiang, and Juan Zhang
[1] Z. Ren, G. Zhang, D. Lin, Z. Zhang, and X. Zhao, Review on application of WSNs, Transducer and Microsystem Technologies, 37(3), 2018, 1–2. [2] Y. Jin, Research on cooperative spectrum sensing technology in cognitive wireless sensor networks (Master’s thesis), Nanjing: Nanjing University of Posts and Telecommunications, 2015 (in Chinese). [3] M. Yang, Design and implementation of wireless sensor network system based on cognitive radio, Fire Control and Command Control, 41(11), 2016, 182–186 (in Chinese). [4] S. Bayhan and Z.F. Alag, A Markovian approach for best-fit channel selection in cognitive radio networks, Ad Hoc Networks, 12, 2014, 165–177. [5] B. Ma, X. Bao, and X. Xie, Spectrum handoff algorithm in cognitive radio networks: A survey, ACTA Electronic Sinica, 44(6), 2016, 1496–1503. [6] D. Darsena, G. Gelli, and F. Verde, An opportunistic spectrum access scheme for multicarrier cognitive sensor networks, IEEE Sensors Journal, 17(8), 2017, 2596–2606. 399 [7] B. Han, H. Jiang, Y. Luo, and J. Zhou, Cognitive radio resource allocation based on the improved quantum genetic algorithm, International Journal of Robotics and Automation, 34(4), 2019, 451–460. [8] J. Ni, X. Li, M. Hua, and S.X. Yang, Bioinspired neural network-based Q-learning approach for robot path planning in unknown environments, International Journal of Robotics and Automation, 31(6), 2016, 4526–4590. [9] H. Chen, Research on channel selection mechanism based on multi-armed bandit in cognitive network (Master’s thesis), Chongqing: Chongqing University of Posts and Telecommunications, 2016 (in Chinese). [10] X. You, X. He, X. Han, C. Wu, and H. Jiang, Cross-layer parameters reconfiguration in industrial cognitive wireless networks using Moabchv algorithm, International Journal of Robotics and Automation, 33(2), 2018, 150–160. [11] P. Auer, N. Cesa-Bianchi, and P. Fischer, Finite-time analysis of the multiarmed bandit problem, Machine Learning, 47(2–3), 2002, 235–256. [12] S.Q. Yahyaa, M.M. Drugan, and B. Manderick, Exploration vs exploitation in the multi-objective multi-armed bandit problem, IEEE 2014 Int. Joint Conf. on Neural Networks, Beijing, China, 2014, 2290–2297. [13] N. Modi, P. Mary, and C. Moy, QoS driven channel election algorithm for cognitive radio network: Multi-user multi-armed bandit approach, IEEE Transactions on Cognitive Communications and Networking, 3(1), 2017, 49–66. [14] Y. Song and J. Xie, Distributed broadcast protocol with collision avoidance in cognitive radio ad hoc networks, Broadcast Design in Cognitive Radio Ad Hoc Networks, (Springer, Cham, 2014), 37–65. [15] Y. Wu and B. Krishnamachari, Online learning to optimize transmission over an unknown Gilbert–Elliott channel, IEEE Int. Symp. on Modeling & Optimization in Mobile, Paderborn, Germany, 2012, 27–32. [16] Z. Juan, J. Hong, H. Zhenhua, C. Chunmei, and J. Hesong, Study of multi-armed bandits for energy conservation in cognitive radio sensor networks, Sensors, 15(4), 2015, 9360–9387. [17] C. Chen, B. Wu, X. Tuo, H. Jiang, and J. Zhang, Relay translation policies based on state pruning for ad hoc networks, International Journal of Robotics and Automation, 33(3), 2018, 247–257. [18] X. Chen, Z. Zhao, and H. Zhang, Stochastic power adaptation with multiagent reinforcement learning for cognitive wireless mesh networks, IEEE Transactions on Mobile Computing, 12(11), 2013, 2155–2166. [19] C. Tekin and M. Liu, Online learning in opportunistic spectrum access: A restless bandit approach, 2011 Proc. IEEE INFOCOM Conf., Shanghai, China, 2011, 2462–2470.
Important Links:
Go Back