The last few years have witnessed a tremendous growth of the demand for wireless services and a significant increase of the number of mobile subscribers. A recent data traffic forecast from Cisco reported that the global mobile data traffic reached 1.2 zettabytes per year in 2016, and the global IP traffic will increase nearly threefold over the next 5 years. Based on these predictions, a 127-fold increase of the IP traffic is expected from 2005 to 2021. It is also anticipated that the mobile data traffic will reach 3.3 zettabytes per year by 2021, and that the number of mobile-connected devices will reach 3.5 per capita.
With such demands for higher data rates and for better quality of service (QoS), fifth generation (5G) standardization initiatives, whose initial phase was specified in June 2018 under the umbrella of Long Term Evolution (LTE) Release 15, have been under vibrant investigation. In particular, the International Telecommunication Union (ITU) has identified three usage scenarios (service categories) for 5G wireless networks: (i) enhanced mobile broadband (eMBB), (ii) ultra-reliable and low latency communications (uRLLC), and (iii) massive machine type communications (mMTC). The vast variety of applications for beyond 5G wireless networks has motivated the necessity of novel and more flexible physical layer (PHY) technologies, which are capable of providing higher spectral and energy efficiencies, as well as reduced transceiver implementations.
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We would like to highlight the second edition of "Time-Frequency Signal Analysis and Processing: A Comprehensive Reference" (https://www.elsevier.com/books/time-frequency-signal-analysis-and-processing/boashash/978-0-12-398499-9) by Professor Boualem Boashash.
Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory, techniques and algorithms used for the analysis and processing of non-stationary signals, as found in a wide range of applications including telecommunications, radar, and biomedical engineering. This book gives the university researcher and R&D engineer insights into how to use TFSAP methods to develop and implement the engineering application systems they require.
About the main editor:
Boualem Boashash (IEEE Fellow '99') is a Scholar, Professor and Senior Academic with experience in 5 leading Universities in France and Australia and 2 universities in the Middle-East. He has published over 500 technical publications, including over 100 journal papers, 3 books and 3 text-books covering Engineering, Applied Mathematics and Medicine. He was an early pioneer of the field of Time–Frequency Signal Processing and he is currently working on the further development of time-frequency theory and medical applications covering mental health and neurosciences with focus on newborn EEG analysis as well as ECG, HRV and fetal movements for improving health outcomes. Among many initiatives, he founded ISSPA, a leading conference since 1985 and its sister workshop WOSSPA. After founding a leading research group at The University of Queensland, he became the Foundation Professor and Director of the Signal Processing Research Centre at the Queensland University of Technology, Brisbane, Australia (1991-2005). He then became the Dean of Engineering at the University of Sharjah, United Arab Emirates (2006-2009) then Associate Dean, Academic at Qatar University and finally a Research Professor. In addition to the teaching, research and management experience, he also has 3 years industrial experience with Elf-Aquitaine in France at the beginning of his career. He is currently Professor at Qatar University, Department of Electrical Engineering, and the leader of a Biomedical Signal Processing group at the School of Medicine, University of Queensland, Brisbane, Australia. He also developed the first software package for time-frequency signal analysis and processing (TFSAP) regularly updated with his co-workers and used by hundreds of researchers around the world. His work has been cited over 10,000 times. Professor Boashash was a member of ICASSP board, associate editor for the IEEE transactions on signal processing and he is currently a member of the Board of the Elsevier journal Digital Signal Processing.
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