@article {28068,
	title = {Incentivizing Resource Cooperation for Blockchain Empowered Wireless Power Transfer in UAV Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {69},
	year = {2020},
	month = {12/2020},
	publisher = { IEEE},
	abstract = {In unmanned aerial vehicle (UAV) networks, UAVs-assisted wireless power transfer is a promising approach to charge low-power smart devices for energy replenishment. However, security and privacy concerns associated with the energy micro-transactions in untrusted wireless trading environment present serious challenges. In this paper, we exploit Directed Acyclic Graph (DAG) and consortium blockchain to propose a new distributed and secure UAVs-assisted wireless power transfer framework named aerial-ground chain, where heterogeneous consensus is developed to verify the energy micro-transactions. Specifically, the UAVs verify energy micro-transactions simultaneously but asynchronously to form an aerial tangle. The smart devices also participate in maintaining the aerial tangle. We define timeout for the energy micro-transactions, and leverage a set of Access Points (APs) to cooperatively confirm the timeout energy micro-transaction by utilizing consortium blockchain, to form a ground main chain. Furthermore, a contract theory based resource cooperation scheme is designed to motivate the UAVs to participate in wireless power transfer, and to incentivize the APs to contribute their resources in cooperatively verifying the timeout energy micro-transactions. Security analysis and numerical results illustrate that the developed aerial-ground chain and the designed contract theory based resource cooperation scheme are secure and efficient for UAVs-assisted wireless power transfer.},
	author = {Jiang, Li and Chen, Bin and Xie, Shengli and Maharjan, Sabita and Zhang, Yan}
}
@article {25824,
	title = {SD-MAC: Spectrum Database-Driven MAC Protocol for Cognitive Machine-to-Machine Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {66},
	year = {2017},
	pages = {1456 - 1467},
	publisher = {IEEE},
	issn = {1939-9359},
	doi = {10.1109/TVT.2016.2555084},
	author = {Liu, Yi and Yu, Rong and Pan, Miao and Zhang, Yan and Xie, Shengli}
}
@article {23727,
	title = {Balancing Power Demand through EV Mobility in Vehicle-to-Grid Mobile Energy Networks},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {12},
	year = {2015},
	month = {02/2016},
	pages = {79-90},
	publisher = {IEEE},
	author = {Yu, Rong and Zhong, Weifeng and Xie, Shengli and Yuen, Chau and Gjessing, Stein and Zhang, Yan}
}
@article {23513,
	title = {Integrated Energy and Spectrum Harvesting for 5G Wireless Communications},
	journal = {IEEE Network},
	volume = {29},
	year = {2015},
	month = {05/2015},
	pages = {75-81},
	publisher = {IEEE},
	author = {Liu, Y. and Zhang, Yan and Yu, Rong and Xie, Shengli}
}
@article {23514,
	title = {MixGroup: Accumulative Pseudonym Exchanging for Location Privacy Enhancement in Vehicular Social Networks},
	journal = {IEEE Transactions on Dependable and Secure Computing},
	volume = {13},
	year = {2015},
	month = {01/2016},
	pages = {93-105},
	publisher = {IEEE},
	author = {Yu, Rong and Kang, Jiawen and Huang, X. and Xie, Shengli and Zhang, Yan and Gjessing, Stein}
}
@article {23515,
	title = {QoS Differential Scheduling in Cognitive Radio Based Smart Grid Networks: An Adaptive Dynamic Programming Approach},
	journal = {IEEE Transactions on Neural Networks and Learning Systems},
	volume = {27},
	year = {2015},
	month = {02/2016},
	pages = {435-443},
	publisher = {IEEE},
	author = {Yu, Rong and Zhong, W. and Xie, Shengli and Zhang, Yan}
}
@article {23518,
	title = {Queuing-Based Energy Consumption Management for Heterogeneous Residential Demands in Smart Grid},
	journal = {IEEE Transaction on Smart Grid},
	year = {2015},
	publisher = {IEEE},
	author = {Liu, Y. and Yuen, C. and Yu, Rong and Zhang, Yan and Xie, Shengli}
}
@article {23495,
	title = {Toward Secure Energy Harvesting Cooperative Networks},
	journal = {IEEE Communications Magazine},
	volume = {53},
	year = {2015},
	month = {08/2015},
	pages = {114-121},
	publisher = {IEEE},
	abstract = {Energy harvesting cooperative networks is an emerging technology that has very high potential for a large variety of applications. However, the energy transfer capability may lead to unprecedented security challenges. In this paper, we will study energy security issues and the solutions in energy harvesting networks. We first identify typical energy related attacks and then propose defense solutions against these attacks. We also carry out security analysis and performance analysis to evaluate our proposed solutions. Simulation results have shownthat the proposed defense solutions are effective and efficient.},
	keywords = {cooperative relay, energy attack, Energy harvesting cooperative networks, security and defense},
	author = {Kang, Jiawen and Yu, Rong and Maharjan, Sabita and Zhang, Yan and Huang, Xumin and Xie, Shengli and Bogucka, Hanna and Gjessing, Stein}
}
@article {Simula.simula.3116,
	title = {A Semiblind Two-Way Training Method for Discriminatory Channel Estimation in MIMO Systems},
	journal = {IEEE Transactions on Communications},
	volume = {62},
	number = {7},
	year = {2014},
	author = {Yang, J. and Xie, Shengli and Zhou, Xing and Yu, Rong and Zhang, Yan}
}
@article {Simula.simula.2418,
	title = {An Efficient MAC Protocol With Selective Grouping and Cooperative Sensing in Cognitive Radio Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {62},
	number = {8},
	year = {2013},
	pages = {3928-3941},
	author = {Liu, Y. and Xie, Shengli and Zhang, Yan and Yu, Rong and Yuen, C.}
}
@article {Simula.simula.1378,
	title = {Cognitive Machine-to-Machine Communications: Visions and Potentials for the Smart Grid},
	journal = {IEEE Network Magazine},
	volume = {26},
	number = {3},
	year = {2012},
	month = {May-June},
	pages = {6-13},
	abstract = {Based upon cognitive radio technology, we propose a new Machine-to-Machine (M2M) communications paradigm, namely Cognitive M2M (CM2M) communication. We first motivate the use of cognitive radio technology in M2M communications from different point of views, including technical, applications, industry support, and standardization perspectives. Then, our CM2M network architecture and cognitive machine model are presented and the CM2M systems coexistence in TV white spaces is discussed. After that, a CM2M communications architecture for the smart grid is presented, for which we also propose an energy-efficiency driven spectrum discovery scheme. Numerical results demonstrate significant energy saving and the reliability in supporting data transmissions in the smart grid.},
	author = {Zhang, Yan and Yu, Rong and Nekovee, M. and Liu, Y. and Xie, Shengli and Gjessing, Stein}
}
@article {Simula.simula.1370,
	title = {Secondary Users Cooperation in Cognitive Radio Networks: Balancing Sensing Accuracy and Efficiency},
	journal = {IEEE Wireless Communications},
	volume = {19},
	number = {2},
	year = {2012},
	pages = {30-37},
	abstract = {Cooperative spectrum sensing is a promising technique in cognitive radio networks by exploiting multi-user diversity to mitigate channel fading. Cooperative sensing is traditionally employed to improve the sensing accuracy while the sensing efficiency has been largely ignored. However, both sensing accuracy and efficiency have very significant impacts on the overall system performance. In this article, we first identify the fundamental trade-off between sensing accuracy and efficiency in spectrum sensing in cognitive radio networks. Then, we present several different cooperation mechanisms, including sequential, full-parallel, semi-parallel, synchronous, and asynchronous cooperative sensing schemes. The proposed cooperation mechanisms and the sensing accuracy-efficiency trade-off in these schemes are elaborated and analyzed with respect to a new performance metric achievable throughput, which simultaneously considers both transmission gain and sensing overhead. Illustrative results indicate that parallel and asynchronous cooperation strategies are able to achieve much higher performance, compared to existing and traditional cooperative spectrum sensing in cognitive radio networks.},
	author = {Yu, Rong and Zhang, Yan and Liu, Y. and Xie, Shengli and Song, L. and Guizani, M.}
}
@article {Simula.simula.950,
	title = {Cognitive Radio Based Hierarchical Communications Infrastructure for Smart Grid},
	journal = {IEEE Network Magazine},
	volume = {25},
	number = {5},
	year = {2011},
	month = {Sept/Oct.},
	author = {Yu, Rong and Zhang, Yan and Gjessing, Stein and Chau, Y. and Xie, Shengli and Guizani, M.}
}
@article {Simula.simula.940,
	title = {Energy-Efficient Spectrum Discovery for Cognitive Radio Green Networks},
	journal = {Mobile Networks and Applications},
	volume = {17},
	number = {1},
	year = {2011},
	pages = {64-74},
	publisher = {Springer},
	author = {Liu, Y. and Xie, Shengli and Zhang, Yan and Yu, Rong and Leung, V.}
}
@article {Simula.simula.936,
	title = {Home M2M Networks: Architectures, Standards, and QoS Improvement},
	journal = {IEEE Communications Magazine},
	volume = {49},
	number = {4},
	year = {2011},
	month = {April},
	pages = {44-52},
	abstract = {It is envisioned that home networks will shift from the current machine-to-human communications to the machineto-machine (M2M) paradigm with the rapid penetration of embedded devices in home surroundings. In this article, we {fi}rst identify the fundamental challenges in home M2M networks. Then, we present the architecture of home M2M networks that is decomposed into three sub-areas depending on the radio service ranges and potential applications. Finally, we focus on the Quality-of-Service (QoS) management in home M2M networks, considering the increasing number of multimedia devices and growing visual requirements in a home area. Three standards for multimedia sharing and their QoS architectures are outlined. A cross-layer joint admission and rate control design is reported for QoS-aware multimedia sharing. This proposed strategy is aware of the QoS requirement and the resilience of multimedia services. Illustrative results indicate that the joint design is able to intelligently allocate radio bandwidth based on QoS demands in resource-constrained home M2M networks.},
	author = {Zhang, Yan and Yu, Rong and Yao, W. and Xie, Shengli and Xiao, Y. and Guizani, M.}
}
@article {Simula.nd.453,
	title = {Cross-Layer Optimized Call Admission Control in Cognitive Radio Networks},
	journal = {Mobile Networks and Applications},
	volume = {15},
	number = {5},
	year = {2010},
	pages = {610-626},
	author = {Yu, Rong and Zhang, Yan and Huang, M. and Xie, Shengli}
}
@inproceedings {Simula.simula.255,
	title = {A Group-Based Cooperative Medium Access Control Protocol for Cognitive Radio Networks},
	journal = {Proceedings of the 18th International Workshop on Quality of Service (IWQoS), 2010},
	year = {2010},
	publisher = {IEEE Press},
	type = {Conference},
	isbn = {978-1-4244-5987-2},
	author = {Liu, Y. and Yu, Rong and Zhang, Yan and Xie, Shengli},
	editor = {B., Liu}
}
@article {Simula.simula.243,
	title = {A Parallel Cooperative Spectrum Sensing in Cognitive Radio Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {59},
	number = {8},
	year = {2010},
	month = {Oct.},
	pages = {4079-4092},
	author = {Xie, Shengli and Liu, Y. and Zhang, Yan and Yu, Rong}
}
@article {Simula.nd.459,
	title = {QoS Differentiated and Fair Packet Scheduling in Broadband Wireless Access Networks},
	journal = {EURASIP Journal on Wireless Communications and Networking},
	volume = {vol. 2009},
	number = {Article ID 482764},
	year = {2009},
	author = {Yu, Rong and Zhang, Yan and Xie, Shengli}
}
