1st Edition

Uncoded Multimedia Transmission

  • Available for pre-order. Item will ship after June 15, 2021
ISBN 9780367632953
June 15, 2021 Forthcoming by CRC Press
344 Pages 128 B/W Illustrations

USD $110.00

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Book Description

An uncoded multimedia transmission (UMT) system is one that skips quantization and entropy coding in compression and all subsequent binary operations, including channel coding and bit-to-symbol mapping of modulation. By directly transmitting non-binary symbols with amplitude modulation, the uncoded system avoids the annoying cliff effect observed in the coded transmission system. This advantage makes uncoded transmission more suited to both unicast in varying channel conditions and multicast to heterogeneous users. In Part I of this book we consider how to improve the efficiency of uncoded transmission and make it on par with the coded transmission. In Part II, we discuss three technologies for multimedia correlation processing in uncoded transmission – Cactus, DCast and LineCast.

All the three pieces of work demonstrate the possibility to build a more robust and efficient wireless multimedia communication system than existing digital ones. In fact, the efficiency of a transmission system is decided by how the resources, including bandwidth, power, and subchannel, are allocated. In Part III, we address the resource allocation problem for UVT in a Rayleigh fading channel, where only statistical channel state information (CSI) is available to the sender. Based on the observation that discarding low-priority (LP) data and saving the channel uses for high-priority (HP) data can significantly improve the quality of the received video, we formulate an optimization problem that aims to minimize the total squared error of a multi-variant Gaussian random vector and find a near optimal solution. Furthermore, the resource allocation problem for UVT is also studied in Non-Orthogonal Multiple Access (NOMA) systems.  

In Part IV, we propose ParCast+ which first separates the source and the channel into independent components, matches the more important source components with higher-gain channel components, and uses amplitude modulation for transmission. In this part of the book, we also consider image and video delivery in MIMO broadcasting networks with diverse channel quality and varying numbers of antennas across receivers In the last part of this book, we investigate the cases where analog transmission can be used in conjunction with digital transmission for a balanced efficiency and adaptation capability. In such a hybrid digital-analog (HDA) system, the two key questions we shall answer are how to separate the video signal into digital and analog parts and how to allocate limited resources between and within digital and analog transmissions.

This book may be used as a collection of research notes for researchers in this field, a reference book for practitioners or engineers, as well as a textbook for a graduate advanced seminar in this fieldor any related fields. The references collected in this book may be used as further reading lists or references for the readers.

Table of Contents

Part I Video Transmission - Coded or Uncoded

1 Uncoded Video Transmission

2 Advances in Uncoded and Hybrid Multimedia Transmission

Part II Correlation Processing

3 Keeping Redundancy in Transmission

4 Distributed Uncoded Video Transmission

5 Line-based Uncoded Image Transmission

Part III Resource Allocation

6 Joint Bandwidth and Power Allocation

7 Progressive Transmission

8 Superposed Transmission with NOMA

9 Joint Subcarrier Matching and Power Allocation

Part IV MIMO Support

10 Channel Allocation

11 Compressive Sampling Code

12 Multiple Similar Description Code

Part V Hybrid Digital and Analog Transmission

13 A Practical HDA Design

14 Structure-Preserving Hybrid Digital-Analog Transmission

15 Superimposed Modulation for Soft Video Delivery with Hidden

16 Adaptive HDA Video Transmission in Wireless Fading Channel



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Feng Wu received his B.S. degree in Electrical Engineering from XIDIAN University in 1992. He received his M.S. and Ph.D. degrees in Computer Science from Harbin Institute of Technology in 1996 and 1999, respectively. Now he is a full professor, the assistant to the president of University of Science and Technology of China (USTC) and the director of National Engineering Laboratory of Brain-Inspired Intelligence Technology and Application (NEL-BITA). Before that, he was a principle researcher and a research manager in Microsoft Research Asia. His research interests include image and video compression, media communication, and media analysis and synthesis. He has authored or co-authored over 300 high quality papers (including about 100 Journal papers) and top conference papers on MOBICOM, SIGIR, CVPR and ACM MM. He has 80 granted US patents. His 15 techniques have been adopted into international video coding standards. His work in Google Scholar has been cited 18000+ (H-index as 54) to date. As a co-author, he got the best paper award in IEEE T-CSVT 2009, IEEE VCIP 2016, PCM 2008 and SPIE VCIP 2007. Wu has been a Fellow of IEEE. He serves or served as, EIC of TCSVT, DEiC of TCSVT, Associate Editors in IEEE TIP, IEEE TCSVT, IEEE TMM, and several other International journals. He also serves/served as General Chair in ICME 2019, TPC Chair in MMSP 2011, VCIP 2010 and PCM 2009.

Dr. Chong Luo joined Microsoft Research Asia (MSRA) in 2003, where she is currently a Principal Researcher with the Intelligent Multimedia Group. She is also an Adjunct Professor and Ph.D. advisor with the University of Science and Technology of China (USTC). Dr. Luo received her Ph.D. degree in Electrical Engineering from Shanghai Jiao Tong University in 2012, M.Sc. degree in Computer Science from National University of Singapore (NUS), Singapore in 2002 and B.Sc. degree in Computer Science from Fudan University, China in 2000. She has been an IEEE senior member since 2014. Dr. Luo has been working on various video-related topics, including peer-to-peer video conferencing, wireless video communications, and multimedia cloud computing. Her current research focus is on building intelligent multimedia systems based on advanced AI technologies. 

Hancheng Lu received his Ph.D. degree from University of Science and Technology of China (USTC) in July 2005, in Communication and Information Systems. He has been a faculty member of USTC since July 2005 and worked as an associate professor at USTC since Jan. 2008. His research interests include multimedia communication and networking, resource optimization in wireless heterogeneous networks. Lu is active in academic volunteer work. He has served as a reviewer for IEEE JSAC, IEEE TWC, IEEE TMM, IEEE T-CSVT, and Technical Program Committee (TPC) member at IEEE ICC, IEEE GLOBECOM, IEEE WCNC.