Real Time Convex Optimisation for 5G Networks and Beyond

Long D. Nguyen is a lecturer at Dong Nai University and adjunct assistant Professor at Duy Tan University, Vietnam. His research interests include convex optimisation techniques for resource management in wireless communications, energy efficiency approaches for 5G networks (heterogeneous networks, relay networks, cell-free networks, and massive MIMO) and real-time optimisation for wireless communication networks and Internet of Things. He holds a PhD in Electronics and Electrical Engineering from Queen's University Belfast, UK. Trung Q. Duong is a professor at Queen's University Belfast, UK, and a Research Chair of Royal Academy of Engineering. His research interests include wireless communications, signal processing, machine learning and optimisation for wireless networks. He serves as editor for IEEE Trans on Wireless Communications and executive editor for IEEE Communications Letters. He received the Royal Academy of Engineering Research Fellowship (2016-2020) and won the Newton Prize in 2017. He is co-editor of the IET book Trusted Communications with Physical Layer Security. Hoang D. Tuan is a professor at the School of Electrical and Data Engineering, University of Technology Sydney, Australia. He has been involved in research on optimisation, control, signal processing, wireless communication, and biomedical engineering for more than 20 years. He received his PhD in Applied Mathematics from Odessa State University, Ukraine.

Chapter 1: Convexity and convex optimisation problems
Chapter 2: Recognition and classification of convex programming
Chapter 3: Convex optimisation for signal processing and wireless communication
Chapter 4: Introduction to real-time embedded optimisation programming
Chapter 5: Introduction to practical optimisation problems
Chapter 6: First-order methods for real-time optimisation
Chapter 7: Distributed and parallel computing for real-time optimisation
Chapter 8: Machine learning for real-time optimisation
Chapter 9: Real-time embedded convex programming
Chapter 10: Real-time embedded optimisation in UAV communications
Chapter 11: An introduction of real-time embedded optimisation programming for UAV systems
Chapter 12: Real-time optimal resource allocation for embedded UAV communication systems
Chapter 13: Real-time deployment and resource allocation for distributed UAV systems in disaster relief
Chapter 14: Practical optimisation of path planning and completion time of data collection for UAV-enabled disaster communications
Chapter 15: Learning-aided real-time performance optimisation of cognitive UAV-assisted disaster communication
References
Appendices