Compressed acquisition and progressive reconstruction of multi-dimensional correlated data in wireless sensor networks

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2014, Pages 6449-6453

  Leinonen, Markus ^a   Codreanu, Marian ^a   Juntti, Markka ^a  

^a UNIVERSITY OF OULU   (Finland)

Author keywords

Compressed sensing; joint signal recovery; Kronecker sparsifying bases; multi hop wireless sensor networks; sliding window processing; spatio temporal correlation

Indexed keywords

COMPRESSED SENSING; DECODING; NUMERICAL METHODS; SIGNAL RECONSTRUCTION;

KRONECKER; MULTIHOP; SIGNAL RECOVERY; SLIDING WINDOW; SPATIOTEMPORAL CORRELATION;

WIRELESS SENSOR NETWORKS;

EID: 84905262911     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2014.6854846     Document Type: Conference Paper

References (24)

1. E. J. Candes, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inform. Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006.
2. E. J. Candes and T. Tao, "Near-optimal signal recovery from random projections: Universal encoding strategies?," IEEE Trans. Inform. Theory, vol. 52, no. 12, pp. 5406-5425, Dec. 2006.
3. D. L. Donoho, "Compressed sensing," IEEE Trans. Inform. Theory, vol. 52, no. 4, pp. 1289-1306, Apr. 2006.
4. J. Haupt and R. Nowak, "Signal reconstruction from noisy random projections," IEEE Trans. Inform. Theory, vol. 52, no. 9, pp. 4036-4048, Sept. 2006.
5. R. G. Baraniuk, "Compressive sensing [lecture notes]," IEEE Signal Processing Mag., vol. 24, no. 4, pp. 118-121, July 2007.
6. E. J Candes and M. B. Wakin, "An introduction to compressive sampling," IEEE Signal Processing Mag., vol. 25, no. 2, pp. 21-30, Mar. 2008.
7. M. F. Duarte, M. B. Wakin, D. Baron, and R. G. Baraniuk, "Universal distributed sensing via random projections," in Proc. IEEE Int. Symp. on Inform. Proc. in Sensor Networks, New York, NY, USA, 2006, pp. 177-185.
8. J. Haupt, W. U. Bajwa, M. Rabbat, and R. Nowak, "Compressed sensing for networked data: A different approach to decentralized compression," IEEE Signal Processing Mag., vol. 25, no. 2, pp. 92-101, Mar. 2008.
9. C. Luo, F. Wu, J. Sun, and C. W. Chen, "Compressive data gathering for large-scale wireless sensor networks," in Proceedings of the 15th annual international conference on Mobile computing and networking, Beijing, China, Sept. 20-25 2009, pp. 145-156.
10. C. Luo, F. Wu, J. Sun, and C. W. Chen, "Efficient measurement generation and pervasive sparsity for compressive data gathering," IEEE Trans. Wireless Commun., vol. 9, no. 12, pp. 3728-3738, Dec. 2010.
11. L. Xiang, J. Luo, and A. Vasilakos, "Compressed data aggregation for energy efficient wireless sensor networks," in Proc. IEEE Int. Conf. Sens., Commun. and Networking, Salt Lake City, USA, June 27-30 2011, pp. 46-54.
12. G. Quer, R. Masiero, G. Pillonetto, M. Rossi, and M. Zorzi, "Sensing, compression, and recovery for WSNs: Sparse signal modeling and monitoring framework," IEEE Trans. Wireless Commun., vol. 11, no. 10, pp. 3447-3461, Oct. 2012.
13. M. Leinonen, M. Codreanu, and M. Juntti, "Distributed correlated data gathering in wireless sensor networks via compressed sensing," in Proc. Annual Asilomar Conf. Signals, Syst., Comp., Pacific Grove, CA, Nov. 3-6 2013.
14. C. Luo, J. Sun, and F. Wu, "Compressive network coding for approximate sensor data gathering," in Proc. IEEE Global Telecommun. Conf., Houston, Texas USA, Dec. 5-9 2011, pp. 1-6.
15. S. Feizi and M. Médard, "A power efficient sensing/ communication scheme: Joint source-channel-network coding by using compressive sensing," CoRR, vol. abs/1110. 0428, available at http://arxiv. org/abs/1110. 0428.
16. D. Baron, M. B. Wakin, M. F. Duarte, S. Sarvotham, and R. G. Baraniuk, "Distributed compressed sensing," Tech. Rep., Nov. 2005.
17. M. F. Duarte and R. G. Baraniuk, "Kronecker compressive sensing," IEEE Trans. Image Processing, vol. 21, no. 2, pp. 494-504, 2012.
18. N. Vaswani and L. Wei, "Modified-CS: Modifying compressive sensing for problems with partially known support," IEEE Trans. Signal Processing, vol. 58, no. 9, pp. 4595-4607, Sept. 2010.
19. W. Lu and N. Vaswani, "Regularized modified BPDN for noisy sparse reconstruction with partial erroneous support and signal value knowledge," IEEE Trans. Signal Processing, vol. 60, no. 1, pp. 182-196, Jan. 2012.
20. M. S. Asif and J. Romberg, "Sparse recovery of streaming signals using l1-homotopy," IEEE Trans. Signal Processing, submitted, 2013, available at http://arxiv. org/abs/1306. 3331.
21. E. J. Candes, "Compressive sampling," in Proceedings of the International Congress of Mathematicians, Madrid, Spain, Aug. 22-30 2006, vol. 3, pp. 1433-1452.
22. J. O. Berger, V. De Oliveira, and B. Sanso, "Objective Bayesian analysis of spatially correlated data," Journal of the American Statistical Association, vol. 96, pp. 1361-1374, Dec. 2000.
23. E. Candes and J. Romberg, "l1-MAGIC: Recovery of sparse signals via convex programming," http://users. ece. gatech. edu/justin/l1magic/, Oct. 2005.
24. M. Grant and S. Boyd, "CVX: Matlab software for disciplined convex programming, version 1. 21," http://cvxr. com/ cvx, Apr. 2011.