Browse > Article
http://dx.doi.org/10.3745/JIPS.03.0028

Sparse Channel Estimation of Single Carrier Frequency Division Multiple Access Based on Compressive Sensing  

Zhong, Yuan-Hong (School of Communication Engineering, Chongqing University)
Huang, Zhi-Yong (School of Communication Engineering, Chongqing University)
Zhu, Bin (School of Communication Engineering, Chongqing University)
Wu, Hua (School of Communication Engineering, Chongqing University)
Publication Information
Journal of Information Processing Systems / v.11, no.3, 2015 , pp. 342-353 More about this Journal
Abstract
It is widely accepted that single carrier frequency division multiple access (SC-FDMA) is an excellent candidate for broadband wireless systems. Channel estimation is one of the key challenges in SC-FDMA, since accurate channel estimation can significantly improve equalization at the receiver and, consequently, enhance the communication performances. In this paper, we study the application of compressive sensing for sparse channel estimation in a SC-FDMA system. By skillfully designing pilots, their patterns, and taking advantages of the sparsity of the channel impulse response, the proposed system realizes channel estimation at a low cost. Simulation results show that it can achieve significantly improved performance in a frequency selective fading sparse channel with fewer pilots.
Keywords
Compressive Sensing; Random Pilot Pattern; SC-FDMA; Sparse Channel Estimation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 3GPP TS 36.201 version 11.1.0, LTE Physical Layer - General description (Release 11), 2013.
2 B. Karakaya, H. Arslan, and H. A, Cirpan, "Channel estimation for LTE uplink in high Doppler spread," in Proceedings of IEEE Wireless Communications and Networking Conference (WCNC 2008), Las Vegas, NV, 2008, pp. 1126-1130.
3 F. S. Al-kamali, M. I. Dessouky, B. M. Sallam, F. Shawki, and F. A. El-Samie, "Uplink single-carrier frequency division multiple access system with joint equalisation and carrier frequency offsets compensation," IET Communications, vol. 5, no. 4, pp. 425-433, 2011.   DOI
4 S. F. Cotter and B. D. Rao, "Sparse channel estimation via matching pursuit with application to equalization," IEEE Transactions on Communications, vol. 50, no. 3, pp. 374-377, 2002.   DOI
5 C. Carbonelli, S. Vedantam, and U. Mitra, "Sparse channel estimation with zero tap detection," IEEE Transactions on Wireless Communications, vol. 6, no. 5, pp. 1743-1763, 2007.   DOI
6 W. U. Bajwa, J. Haupt, A. M. Sayeed, and R. Nowak, "Compressed channel sensing: a new approach to estimating sparse multipath channels," Proceedings of the IEEE, vol. 98, no. 6, pp. 1058-1076. 2010.   DOI
7 C. R. Berger, Z. Wang, J. Huang, and S. Zhou, "Application of compressive sensing to sparse channel estimation," IEEE Communications Magazine, vol. 48, no. 11, pp. 164-174, 2010.   DOI
8 D. L. Donoho, "Compressed sensing," IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289-1306, 2006.   DOI
9 X. Zhou, Y. Fang, and M. Wang, "Compressed sensing based channel estimation for fast fading OFDM systems," Journal of Systems Engineering and Electronics, vol. 21, no. 4, pp. 550-556, 2010.   DOI
10 J. Meng, W. Yin, Y. Li, N. T. Nguyen, and Z. Han, "Compressive sensing based high-resolution channel estimation for OFDM system," IEEE Journal of Selected Topics in Signal Processing, vol. 6, no. 1, pp. 15-25, 2012.   DOI
11 G. Taubock and F. Hlawatsch, "A compressed sensing technique for OFDM channel estimation in mobile environments: exploiting channel sparsity for reducing pilots," in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), Las Vegas, NV, 2008, pp. 2885-2888.
12 X. He, R. Song, and W. P. Zhu, "Optimal pilot pattern design for compressed sensing-based sparse channel estimation in OFDM systems," Circuits, Systems, and Signal Processing, vol. 31, no. 4, pp. 1379-1395, 2012.   DOI
13 C. T. Lam, D. D. Falconer, F. Danilo-Lemoine, and R. Dinis, "Channel estimation for SC-FDE systems using frequency domain multiplexed pilots," in Proceedings of 2006 IEEE 64th Vehicular Technology Conference (VTC- 2006 Fall), Montreal, Canada, 2006, pp. 1-5.
14 S. S. Chen, D. L. Donoho, and M. A. Saunders, "Atomic decomposition by basis pursuit," SIAM Journal on Scientific Computing, vol. 20, no. 1, pp. 33-61, 1998.   DOI
15 E. J. Candes, "The restricted isometry property and its implications for compressed sensing," Comptes Rendus Mathematique, vol. 346, no. 9, pp. 589-592, 2008.   DOI
16 E. J. Candès, J. Romberg, and T. Tao, "Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information," IEEE Transactions on Information Theory, vol. 52. no. 2, pp. 489-509, 2006.   DOI
17 D. L. Donoho, M. Elad, and V. N. Temlyakov, "Stable recovery of sparse overcomplete representations in the presence of noise," IEEE Transactions on Information Theory, vol. 52, no. 1, pp. 6-18, 2006.   DOI
18 J. A. Tropp and A. C. Gilbert, "Signal recovery from partial information via orthogonal matching pursuit" Apr. 2005; http://www.math.lsa.umich.edu/-annacg/papers/TG05-Signal-Recovery.pdf.
19 J. A. Tropp, "Just relax: convex programming methods for identifying sparse signals in noise," IEEE Transactions on Information Theory, vol. 52, no. 3, pp. 1030-1051, 2006.   DOI
20 S. G. Mallat and Z. Zhang, "Matching pursuits with time-frequency dictionaries," IEEE Transactions on Signal Processing, vol. 41, no. 12, pp. 3397-3415, 1993.   DOI
21 D. Needell and J. A. Tropp, "CoSaMP: iterative signal recovery from incomplete and inaccurate samples," Applied and Computational Harmonic Analysis, vol. 26, no. 3, pp. 301-321, 2009.   DOI
22 S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory. Englewood Cliffs, NJ: Prentice-Hall, 1998.
23 M. Sharp and A. Scaglione, "Estimation of sparse multipath channels," in Proceedings of IEEE Military Communications Conference (MILCOM 2008), San Diego, CA, 2008, pp. 1-7.
24 H. G. Myung, J. Lim, and D. Goodman, "Single carrier FDMA for uplink wireless transmission," IEEE Vehicular Technology Magazine, vol. 1, no. 3, pp. 30-38, 2006.   DOI
25 J. G. Proakis and M. Salehi, Digital Communication, 5th ed. Dubuque, IA: McGraw-Hill, 2007.