Scalable compressive sensing-based multi-user detection scheme for Internet-of-Things applications

IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation

Volumn 2015-December, Issue , 2015, Pages

  Liu, Jiachen ^a   Cheng, Hung Yi ^a   Liao, Ching Chun ^a   Wu, An Yeu Andy ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

compressive sensing; Internet of Things; multi user detection; multiple measurement vector; user activity sparsity

Indexed keywords

BIT ERROR RATE; CODE DIVISION MULTIPLE ACCESS; COMPRESSED SENSING; HARDWARE; INTERNET; MULTIUSER DETECTION; RECONFIGURABLE HARDWARE; SENSOR NODES; SIGNAL DETECTION; SIGNAL PROCESSING; SIGNAL RECONSTRUCTION; SPECTROSCOPY;

COMPRESSIVE SENSING; HUMAN COMMUNICATIONS; INTERNET OF THINGS (IOT); MACHINE-TO-MACHINE COMMUNICATIONS; MEMORY REDUCTION; MULTIPLE MEASUREMENT VECTORS; SPREAD-SPECTRUM PROTOCOLS; USER ACTIVITY;

INTERNET OF THINGS;

EID: 84958212400     PISSN: 15206130     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SiPS.2015.7345002     Document Type: Conference Paper

References (10)

1. E. Fleisch, What is the internet of things? An economic perspective, Economics, Management, and Financial Markets, vol. 5, no. 2, pp. 125-157, 2010
2. A. Zanella et al., "M2M massive wireless access: challenges, research issues, and ways forward," 2013 IEEE Globecom Workshops, Atlanda, GA, 2013, pp.151-156
3. S. Verdu, Multiuser Detection. 2nd ed. New York: Cambridge University Press, 2003
4. F. Monsees, C. Bockelmann, D. Wubben, and A. Dekorsy, "Sparsity aware multiuser detection for machine to machine communication," 2012 IEEE Globecom Workshops, Anaheim, CA, 2012, pp. 3-7
5. C. Bockelmann, H. F. Schepker, and A. Dekorsy, "Compressive sensing based multi-user detection for machine-to-machine communication," Transactions on Emerging Telecommunications Technologies, vol. 24, no. 4, pp. 389-400, 2013
6. E. J. Candès and M. B. Wakin, "An introduction to compressive sampling," IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 21-30, 2008
7. G. Swirszcz, N. Abe, and A. C. Lozano, "Grouped orthogonal matching pursuit for variable selection and prediction," Advances in Neural Information Processing Systems, 2009, pp. 1150-1158
8. R. Maleh, "Efficient sparse approximation methods for medical imaging", Ph.D. dissertation, Applied and Interdisciplinary Mathematics, University of Michigan, Ann Harbor, MI, 2009
9. J. A. Tropp, A. C. Gilbert, M. J. Strauss, "Simultaneous sparse approximation via greedy pursuit," 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, Proceedings, vol. 5, pp. 721-724, March 2005
10. T. T. Cai and Lie Wang, "Orthogonal matching pursuit for sparse signal recovery with noise," IEEE Transactions on Information Theory, vol. 57, no. 7, pp. 4680-4688, July 2011