Title Recent Advances in Information, Communications and Signal Processing
Subtitle (River Publishers Series in Signal, Image and Speech Processing)
Author Andy W. H. Khong, Yong Liang Guan
ISBN 9788793609433
List price USD 125.00
Price outside India Available on Request
Original price
Binding Hardbound
No of pages 200
Book size 153 x 229 mm
Publishing year 2018
Original publisher River Publishers (Eurospan Group)
Published in India by .
Exclusive distributors Viva Books Private Limited
Sales territory India, Sri Lanka, Bangladesh, Pakistan, Nepal, .
Status New Arrival
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Research in information, communications and signal processing has brought about new services, applications and functions in a large number of fields which include consumer electronics, biomedical devices and defence. These applications play an important role in advancing technologies to enhance human life in general.

Recent Advances in Information, Communications and Signal Processing aims to give students, researchers, and engineers information pertaining to recent advances in these fields. In terms of research in signal processing topics, the two chapters included in this book have a strong emphasis on advances in algorithmic development in the biomedical, and human-computer interfaces domain areas. More specifically, the use of deep learning for placental maturity staging is discussed as well as the use of vibration analysis for localising impacts on surfaces for human-computer applications. In terms of communications signal processing, advances in new wireless communication such as NOMA (non-orthogonal multiple access) and millimetre-wave antenna design for 5G cellular mobile radio, as well as innovations in LDPC (low density parity check code) decoding and networking coding, are featured.




List of Contributors

List of Figures

List of Tables

List of Notations

List of Abbreviations

Chapter 1: Non-orthogonal Multiple Access: Recent Developments and Future Trends
A. Anwar, B.-C. Seet and X. J. Li.

Introduction • Classification of NOMA Schemes • NOMA via Code Domain Multiplexing • Low density spreading CDMA • Low density spreading OFDM • Sparse code multiple access • Multi-user shared access • Interleave-division multiple access • NOMA via Power Domain Multiplexing • NOMA • Basic Principle • NOMA Transmitter and Receiver Architectures • Motivations to Adopt NOMA as MA Scheme for 5G • Review of Some Recent Developments for NOMA • Throughput and Outage Analysis • Power Allocation and User Grouping • Fairness in NOMA • MIMO NOMA • Massive MIMO NOMA • Cooperation in NOMA • NOMA for Relaying Networks • NOMA and Simultaneous Wireless Information and Power Transfer • Performance-limiting Factors for Existing NOMA • Proposed PIC-based Receiver Structure • Performance Comparison • Future Research Direction • Modulation and Coding Scheme • Hybrid MA • Imperfect CSI • Cross Layer Optimization • HARQ Design for NOMA • Massive MIMO NOMA • Full Duplex NOMA • Conclusion • References

Chapter 2: Beam Steering MIMO Antenna for Mobile Phone of 5G Cellular Communications Operating at MM-Wave Frequencies: Design
T Thomas, Peter Gardner, Alexandros Feresidis and K Veeraswamy

Introduction • The th-Generation Cellular Mobile Communications • Design Issues at Base Station for 5G Cellular Mobile Communication System • Design Issues at User Equipment for 5G Cellular Mobile Communication System • Applications and Techniques Supported by 5G Technology • Proposed Antenna: Design and Analysis • Proposed MIMO Antenna Model #1 • Proposed MIMO Antenna Model #2 • Proposed MIMO Antenna Model #3 • Conclusion • References

Chapter 3: Random Linear Network Coding with Source Precoding for Multi-session Networks
Xiaoli Xu, Yong Zeng and Yong L. Guan

Introduction • Network Model with RLNC • Precoder Design and Achievable Rate Region for Double-Unicast Networks • An Optimal Achievable Rate Region with RLNC • A Linear Capacity-achieving Scheme • An Achievable Region in Terms of Min-cuts • Joint Routing and RLNC • Asymptotic Capacity-achieving for Multi-source Erasure Networks • The Capacity Region • Asymptotical Capacity-achieving with RLNC • Time-extended networks • Linear finite-field MAC • Multi-source Erasure Network with Broadcast Channels • General Model for Wireless Erasure Networks • Notes and Further Reading • Appendix • References

Chapter 4: Decoding Scheduling for Low-Density Parity-Check Codes
Huang-Chang Lee, Yen-Ming Chen and Yeong-Luh Ueng

Introduction • Belief Propagation Decoding for LDPC Codes • Fixed Schedules • The Flooding Schedule • Standard Sequential Schedules • Decoding Schedules for Faster Convergence • Protograph-based LDPC Codes • Protograph-based Edge-wise Schedule • The M212-based Algorithm • High-order Prediction for the M212-based Algorithm • Performance Evaluation • A Reduction of the Complexity for Scheduling Arrangement • Performance Evaluation for the M212-based Algorithm • Lower Error Floor via Schedule Diversity • Decoding Scheme Combined with Schedule Diversity • Comparison with Other Error Floor Lowering Techniques • Remarks • References

Chapter 5: Location Template Matching on Rigid Surfaces for Human—Computer Touch Interface Applications
Nguyen Q. Hanh, V. G. Reju and Andy W. H. Khong

Introduction • LTM for Impact Localization on Solids • Time-reversal Theory-based LTM • Classical Plate Theory-based LTM • All-pole Filter Model-based LTM (AP-LTM) • Zak Transform for Time-frequency-based LTM (Z-LTM) • Noise-robust LTM Using Band-limited Components • Band-limited Components as Location-dependent Features • The BLC-LTM Algorithm • Experiment Results • Concluding Remarks • References

Chapter 6: Automatic Placental Maturity Grading via Deep Convolutional Networks
Baiying Lei, Feng Jiang, Yuan Yao, Wanjun Li, Siping Chen, Dong Ni and Tianfu Wang

Introduction • Related Work • Methodology • Convolutional Neural Network • Convolution • Down-sampling • Activation functions • Automatic Grading Algorithm Based on CNN • Framework • Data augmentation • Transfer learning • Feature visualization • Experiments • Experimental Settings • Experimental Results • Result Analysis • Conclusion • References


About the Editors

About the Editors:

Andy Khong is currently an Associate Professor in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He obtained his Ph.D. from Imperial College London and his B.Eng. from Nanyang Technological University, Singapore. His postdoctoral research involved the development of signal processing algorithms for acoustic microphone array and seismic sensors in perimeter security systems. His Ph.D. research was mainly on adaptive ?ltering algorithms. He has also published works on speech enhancement, multi-channel microphone array and blind deconvolution algorithms. His other research interest includes education data mining, machine learning applied to education data. Andy currently serves as an Associate Editor in the IEEE Trans. Audio, Speech and Language Processing and the Journal of Multidimensional Systems and Signal Processing (Springer). He is the author/co-author of three papers awarded the “Best Student Paper Awards”.

Yong Liang Guan, Nanyang Technological University, Singapore

Target Audience:

People interested in Signal processing, deep neural networks, source localisation, mechanical vibration analysis, non-orthogonal multiple access, millimetre-wave communication, low density parity check code, network coding.


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