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