Cognitive radio networks (CRN) will be widely deployed in the near future, and this SpringerBrief covers some important aspects of it, as well as highlighting optimization strategies in Resource Allocation and Spectrum Sensing in CRNs. The cognitive approach in radio access is introduced in the first part of this SpringerBrief, and then next the benefits of cooperative spectrum sensing are highlighted and a framework for studying it under realistic channel conditions is described. New exact closed-form expressions for average false alarm probability and average detection probability are derived in this scenario. A novel approximation to alleviate the computational complexity of the proposed models are also discussed. Once the spectrum opportunities are identified, efficient and systematic resource allocation (RA) shall be performed. The second part of this SpringerBrief describes the taxonomy for the RA process in CRN. A comprehensive overview of the optimization strategies of the CRN RA is also provided. The device-to-device (D2D) communication scenario is discussed, then as a case study and various optimization strategies for the application of the CR technology in the D2D realm is studied. The application of advanced geometric water-filling (GWF) approach in CRN D2D environment for optimum resource allocation is presented in detail. Numerical results provide more insight quantitatively. Overall, this book is suitable for a wide audience that include students, faculty and researchers in wireless communication area and professionals in the wireless service industry.

This book investigates intelligent network resource management for IoV, with the objective of maximizing the communication and computing performance of vehicle users. Focusing on two representative use cases in IoV, i.e., safety message broadcast and autonomous driving, the authors propose link-layer protocol design and application-layer computing task scheduling to achieve the objective given the unique characteristics and requirements of IoV. In particular, this book illustrates the challenges of resource management for IoV due to network dynamics, such as time-varying traffic intensity and vehicle mobility, and presents intelligent resource management solutions to adapt to the network dynamics. The Internet of Vehicles (IoV) enables vehicle-to-everything connectivity and supports a variety of applications for vehicles on the road. Intelligent resource management is critical for satisfying demanding communication and computing requirements on IoV, while the highly dynamic network environments pose challenges to the design of resource management schemes. This book provides insights into the significance of adaptive resource management in improving the performance of IoV. The customized communication protocol and computing scheduling scheme are designed accordingly by taking the network dynamics information as an integral design factor. Moreover, the decentralized designs of the proposed solutions guarantee low signaling overhead and high scalability. A comprehensive literature review summarizing recent resource management schemes in IoV, followed by the customized design of communication and computing solutions for the two IoV use cases is included which can serve as a useful reference for professionals from both academia and industry in the area of IoV and resource management. Researchers working within this field and computer science and electrical engineering students will find this book useful as well.