Joint channel estimation and data detection in MIMO-OFDM using distributed compressive sensing

K. Charly Jomon; S. Prasanth

doi:10.3103/S0735272717020029

Authors

K. Charly Jomon IES College of Engineering, India https://orcid.org/0000-0002-1294-2420
S. Prasanth Royal College of Engineering and Technology, Akkikavu, India

DOI:

https://doi.org/10.3103/S0735272717020029

Keywords:

MIMO, OFDM, distributed compressive sensing, sparse Bayesian learning

Abstract

Channel impulse response of a multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) channel contains a smaller number of nonzero components. In addition, locations of nonzero taps coincide in delay domain. So channel impulse responses can be modeled into an approximately group sparse signals. In this work we use extended sparse Bayesian learning (ESBL), a new method for multichannel compressive sensing for channel estimation in MIMO-OFDM. In joint extended sparse Bayesian learning (JESBL), both pilot and data subcarriers are utilized for channel estimation. These methods can reduce the number of pilot subcarriers in OFDM and improve the spectral efficiency of the MIMO-OFDM system.

References

EIWEN, DANIEL; TAUBOCK, GEORG; HLAWATSCH, FRANZ; RAUHUT, HOLGER; CZINK, NICOLAI. Multichannel-compressive estimation of doubly selective channels in MIMO-OFDM systems: Exploiting and enhancing joint sparsity. Proc. of IEEE Int. Conf. on Acoustics Speech and Signal Processing, ICASSP, 14-19 Mar. 2011. doi:http://dx.doi.org/10.1109/ICASSP.2010.5496098.

PRASAD, RANJITHA; MURTHY, CHANDRA R.; RAO, BHASKAR D. Joint approximately sparse channel estimation and data detection in OFDM systems using sparse Bayesian learning. IEEE Trans. Signal Process., v.62, n.14, p.3591-3603, 2014. doi:http://dx.doi.org/10.1109/TSP.2014.2329272.

PRASAD, RANJITHA; MURTHY, CHANDRA R. Bayesian learning for joint sparse OFDM channel estimation and data detection. Proc. of IEEE Conf. on Global Telecommunications, GLOBECOM, 6-10 Dec. 2010, Miami, FL, USA. IEEE, 2010, p.1-6. doi:http://dx.doi.org/10.1109/glocom.2010.5683775.

COLERI, SINEM; ERGEN, MUSTAFA; PURI, ANUJ; BAHAI, AHMAD. Channel estimation techniques based on pilot arrangement in OFDM systems. IEEE Trans. Broadcasting, v.48, n.3, p.223-229, 2002. doi:http://dx.doi.org/10.1109/TBC.2002.804034.

BARBOTIN, YANN; HORMATI, ALI; RANGAN, SUNDEEP; VETTERLI, MARTIN. Estimating sparse MIMO channels having common support. Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, 22-27 May 2011. IEEE, 2011. doi:http://dx.doi.org/10.1109/icassp.2011.5946268.

ZHANG, ZHILIN; RAO, BHASKAR D. Sparse signal recovery with temporally correlated source vectors using sparse Bayesian learning. IEEE J. Selected Topics Signal Processing, v.5, n.5, p.912-926, 2011. doi:http://dx.doi.org/10.1109/JSTSP.2011.2159773.