PREFACE
DEDICATIONACKNOWLEDGEMENTSNOMENCLATURETABLE OF CONTENTS
I INTRODUCTION 1.1 Introduction to MIMO System 1.2 Challenges and Motivation 1.3 Contributions 1.4 Book Outline
II BACKGROUND2.1 MIMO System Model 2.2 MIMO Detection Scheme 2.2.1 Optimal MIMO Detection 2.2.2 Sub-optimal MIMO Detection 2.2.3. Near Optimal MIMO Detection
III REAL DOMAIN ITERATIVE K-BEST DETECTOR
3.1 Theory of K-Best Algorithm 3.2 Proposed K-Best Algorithm 3.2.1 LR-aided K-Best Decoder 3.2.2 On Demand Child Expansion 3.2.3 Soft Decoding 3.2.4 LDPC Decoder 3.3 Discussion 3.3.1 Simulation and Analysis 3.3.2 Choosing Optimum List Size, K 3.3.3 Effect of LLR Clipping on K
IV COMPLEX DOMAIN ITERATIVE K-BEST DECODER
4.1 Proposed Complex domain K-Best Decoder 4.2 Complex On-demand Expansion 4.3 Iterative Soft Decoding 4.4 Discussion 4.4.1 Simulation and Analysis 4.4.2 Effect of Rlimit on BER 4.4.3 Comparison of Performance
V FIXED POINT REALIZATION OF ITERATIVE K-BEST DECODER
5.1 Architecture Selection 5.1.1 QR Decomposition 5.1.2 Lattice Reduction 5.1.3 LDPC Decoder 5.2 Fixed Point Conversion with Word-length Optimization 5.3 Discussion 5.3.1 Comparison of Performance 5.3.2 Optimization of Word-length
VII ADAPTIVE REAL DOMAIN ITERATIVE K-BEST DECODER 6.1 Proposed Adaptive K-Best Algorithm 6.2 Discussion 6.2.1 Estimation of Channel 6.2.2 Choosing Threshold Points 6.2.3 Performance of Adaptive K-Best Decoder
VII CONCLUSION
7.1 Summary of Chapter II 7.1.1 MIMO System Model 7.1.2 MIMO Detection Schemes 7.2 Summary of Chapter III 7.2.1 Discussion of Chapter III 7.3 Summary of Chapter IV 7.3.1 Discussion of Chapter IV 7.4 Summary of Chapter V 7.4.1 Discussion of Chapter V 7.5 Summary of Chapter VI 7.5.1 Discussion of Chapter VI REFERENCES
About the Author: Mehnaz Rahman completed her Bachelor of Science on Electrical and Electronics Engineering from Bangladesh University of Engineering and Technology in 2011. She is currently doing PhD in Computer Engineering from Texas A&M University, College Station, TX since Fall 2012 under the supervision of Dr. Gwan Choi. Her research interest is focused on algorithmic development and circuit level VLSI design for beyond 5G wireless communication.
After completion of her BSC degree, she worked at Samsung R&D Center, Dhaka, Bangladesh in 2011. She also did summer internships at Intel Research Lab in every year from 2013 to 2015. She has worked as a Teaching Assistant at TAMU for a variety of undergraduate and graduate courses and has been nominated for the Best TA Award during spring 2015. She has received Intel Research Award during her internship in summer, 2013 and Graduate Merit Award at TAMU during fall 2015 for her achievement on research. She has also filed a patent on 5G+ wireless technology with Intel Lab.
Dr. Gwan Choi received his B.S., M.S. and Ph.D. degrees, all in electrical and computer engineering, from the University of Illinois at Urbana-Champaign in 1988, 1989 and 1994, respectively. He currently is an associate professor in the department. He has worked for Cray Research Inc. and Tandem Computers Inc, and he has been a visiting scientist at the NASA Langley Research Center.
Dr. Choi's research interests include fault-tolerance, verification simulation, high-performance VLSI circuits, radiation testing, design for dependability and software engineering. He is a member of Eta Kappa Nu, the IEEE Computer Society, the IEEE technical committee on Fault-Tolerant Computing and the IEEE technical committee on computer architecture.
Dr. Choi also has served as a program committee member on several international conferences and was a vice-chair for the IEEE International Performance and Dependability Symposium, IPDS-2000. He has won a number of awards including the National Science Foundation's (NSF) career award in 1997.
