Due to ever increasing usage of wireless devices and data hungry applications, it has become necessary to improve the spectral efficiency of existing wireless networks. One way of improving spectral efficiency is to share the spectrum amongst different coexisting networks and serve multiple devices simultaneously. Spectrum sharing mechanisms for coexistence of a licensed network, such as LTE, with an unlicensed network, such as Wi-Fi, are being considered in the recent literature and standardizations. In order to enable the coexistence between licensed and unlicensed users, it is necessary to include interference mitigation techniques to protect the licensed primary users (PUs) from harmful interference. Typical interference mitigation mechanisms are based on spectrum sensing and cognitive radio (CR), wherein unlicensed secondary users (SUs) observe the spectrum and utilize it when licensed PUs are inactive. Thus, the SUs utilize empty time-slots in the shared spectrum to avoid the interference. The spectral efficiency can be further improved if the SUs are allowed to transmit concurrently with PUs by exploiting the spatial dimension provided by multiple antenna techniques. The underlay CR paradigm allows such coexistence where SUs transmit its signal in the same time-slots as PUs by exploiting the spatial and frequency resources in the network. In order to exploit the spatial dimension, SUs can utilize the location coordinates of PUs to steer its signal away from PUs to mitigate the interference. The SU transmitter can also employ multiple antenna techniques to serve a large number of devices. Further, the SUs can utilize frequency bands occupied by PUs by dynamically selecting the frequency band that provides the highest rate. In this work, we develop techniques for PU location estimation, spatial resource allocation and frequency band selection for SUs in underlay CR networks.
Performance Optimization of Energy-Harvesting Underlay Cognitive Radio Networks Using Reinforcement Learning
Department of Computer and Software Engineering, Polytechnique Montreal（蒙特利尔理工学院计算机与软件工程系）；Department of Electrical and Computer Engineering, Concordia University（Concordia大学电气与计算机工程系）
Exploiting Self-Sustainable Information-Bearing RIS in Underlay CR-NOMA Networks
School of Electronics and Information Engineering, Harbin Institute of Technology（哈尔滨工业大学电子与信息工程学院）；China-Chile ICT “Belt and Road” Joint Laboratory（中智ICT“一带一路”联合实验室）；University College London（伦敦大学学院）；The University of Hong Kong（香港大学）
