Abstract
Lens antenna array is considered as an effective beam selection mechanism in millimeter wave massive multiple input multiple output systems. Efficient channel estimation (CE) algorithms are required to use the advantage of the beam selection paradigm. Recently, compressive sensing-based algorithms are used to utilize existing sparsity for CE in these systems. Among them, orthogonal matching pursuit (OMP) and support detection (SD) are the most popular ones. These two popular algorithms have their own advantages and disadvantages. In this paper, we propose to use OMP and SD together for better CE. Simulations validate that the proposed algorithm enhances the CE quality over the conventional algorithms. These simulations are tested over two popularly used channel models.
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p is founded experimentally in the next section by considering the generalizability and performance of the proposed algorithm.
References
3rd Generation Partnership Project (3GPP): Spatial channel model for multiple input multiple output (MIMO) simulations (2014). Document 25.996 Version 12.0.0 Release 12
Alkhateeb, A., Ayach, O.E., Leus, G., Heath, R.W.: Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE J. Sel. Topics Signal Process. 8(5), 831–846 (2014). https://doi.org/10.1109/JSTSP.2014.2334278
Alkhateeb, A., Leus, G., Heath, R.W.: Compressed sensing based multi-user millimeter wave systems: How many measurements are needed? In: Proc. IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP), pp. 2909–2913 (2015). https://doi.org/10.1109/ICASSP.2015.7178503
Alkhateeb, A., Mo, J., Gonzalez-Prelcic, N., Heath, R.W.: MIMO precoding and combining solutions for millimeter-wave systems. IEEE Commun. Mag. 52(12), 122–131 (2014). https://doi.org/10.1109/MCOM.2014.6979963
Ayach, O.E., Rajagopal, S., Abu-Surra, S., Pi, Z., Heath, R.W.: Spatially sparse precoding in millimeter wave MIMO systems. IEEE Trans. Wireless Commun. 13(3), 1499–1513 (2014). https://doi.org/10.1109/TWC.2014.011714.130846
Björnson, E., Hoydis, J., Sanguinetti, L.: Massive MIMO networks: Spectral, energy, and hardware efficiency. Found. Trends Signal Process. 11(3–4), 154–655 (2017). https://doi.org/10.1561/2000000093
Brady, J., Behdad, N., Sayeed, A.M.: Beamspace MIMO for millimeter-wave communications: system architecture, modeling, analysis, and measurements. IEEE Trans. Antennas Propag. 61(7), 3814–3827 (2013). https://doi.org/10.1109/TAP.2013.2254442
Chen, S.S., Donoho, D.L., Saunders, M.A.: Atomic decomposition by basis pursuit. SIAM Rev. 43(1), 129–159 (2001). https://doi.org/10.1137/S003614450037906X
Dai, L., Gao, X., Han, S., Chih-Lin, I., Wang, X.: Beamspace channel estimation for millimeter-wave massive mimo systems with lens antenna array. In: Proc. IEEE/CIC ICCC, pp. 1–6 (2016). https://doi.org/10.1109/ICCChina.2016.7636854
Ding, Y., Rao, B.D.: Dictionary learning-based sparse channel representation and estimation for FDD massive MIMO systems. IEEE Trans. Wireless Commun. 17(8), 5437–5451 (2018). https://doi.org/10.1109/TWC.2018.2843786
Ertel, R.B., Cardieri, P., Sowerby, K.W., Rappaport, T.S., Reed, J.H.: Overview of spatial channel models for antenna array communication systems. IEEE Pers. Commun. 5(1), 10–22 (1998). https://doi.org/10.1109/98.656151
Gao, X., Dai, L., Han, S., I, C.L., Wang,: X.: Reliable beamspace channel estimation for millimeter-wave massive MIMO systems with lens antenna array. IEEE Trans. Wireless Commun 16(9), 6010–6021 (2017). https://doi.org/10.1109/TWC.2017.2718502
Gao, Z., Dai, L., Mi, D., Wang, Z., Imran, M.A., Shakir, M.Z.: Mmwave massive-MIMO-based wireless backhaul for the 5G ultra-dense network. IEEE Wireless Commun. 22(5), 13–21 (2015). https://doi.org/10.1109/MWC.2015.7306533
Han, S., Chih-Lin, I., Xu, Z., Rowell, C.: Large-scale antenna systems with hybrid analog and digital beamforming for millimeter wave 5G. IEEE Commun. Mag. 53(1), 186–194 (2015). https://doi.org/10.1109/MCOM.2015.7010533
Heath, R.W., Gonzalez-Prelcic, N., Rangan, S., Roh, W., Sayeed, A.M.: An overview of signal processing techniques for millimeter wave MIMO systems. IEEE J. Sel. Topics Signal Process. 10(3), 436–453 (2016). https://doi.org/10.1109/JSTSP.2016.2523924
Kim, T., Love, D.J.: Virtual AoA and AoD estimation for sparse millimeter wave MIMO channels. In: Proc. Int. Wksh. Signal Process. Adv. Wireless Commun. (SPAWC), pp. 146–150 (2015). https://doi.org/10.1109/SPAWC.2015.7227017
Kim, T., Love, D.J.: Virtual AoA and AoD estimation for sparse millimeter wave MIMO channels. In: Proc. SPAWC Workshops, pp. 146–150 (2015). https://doi.org/10.1109/SPAWC.2015.7227017
Kotecha, J.H., Sayeed, A.M.: Transmit signal design for optimal estimation of correlated MIMO channels. IEEE Trans. Signal Process. 52(2), 546–557 (2004). https://doi.org/10.1109/TSP.2003.821104
Kutty, S., Sen, D.: Beamforming for millimeter wave communications: an inclusive survey. IEEE Commun. Surv. Tuts. 18(2), 949–973 (2015). https://doi.org/10.1109/COMST.2015.2504600
Molisch, A.F., Kuchar, A., Laurila, J., Hugl, K., Schmalenberger, R.: Geometry-based directional model for mobile radio channels-principles and implementation. Eur. Trans. Telecommun. 14(4), 351–359 (2003). https://doi.org/10.1002/ett.928
Nazzal, M., Aygül, M.A., Arslan, H.: Channel modeling for 5G and beyond. Flexible cognitive radio access technologies 5G beyond, p. 341 (2020). https://doi.org/10.1049/pbte092e_ch11
Pati, Y.C., Rezaiifar, R., Krishnaprasad, P.S.: Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition. In: Proc. 27th Ann. Asilomar Conf. Signals Syst. Comput., pp. 40–44. Pacific Grove, CA, Nov (1993). https://doi.org/10.1109/ACSSC.1993.342465
Pi, Z., Khan, F.: An introduction to millimeter-wave mobile broadband systems. IEEE Commun. Mag. 49(6), 101–107 (2011). https://doi.org/10.1109/MCOM.2011.5783993
Rappaport, T.S., Murdock, J.N., Gutierrez, F.: State of the art in 60-GHz integrated circuits and systems for wireless communications. Proc. IEEE 99(8), 1390–1436 (2011). https://doi.org/10.1109/JPROC.2011.2143650
Rusek, F., Persson, D., Lau, B.K., Larsson, E.G., Marzetta, T.L., Edfors, O., Tufvesson, F.: Scaling up MIMO: Opportunities and challenges with very large arrays. IEEE Signal Process. Mag. 30(1), 40–60 (2013). https://doi.org/10.1109/MSP.2011.2178495
Sayeed, A., Behdad, N.: Continuous aperture phased mimo: basic theory and applications. In: Proceedings of the 48th Annual Allerton Conference Communications Control, Computing (Allerton), pp. 1196–1203. IEEE (2010). https://doi.org/10.1109/ALLERTON.2010.5707050
Sayeed, A., Brady, J.: Beamspace MIMO for high-dimensional multiuser communication at millimeter-wave frequencies. Proc. IEEE Global Commun. Conf. GLOBECOM, 3679–3684 (2013). https://doi.org/10.1109/GLOCOM.2013.6831645
Sayeed, A.M.: Deconstructing multiantenna fading channels. IEEE Trans. Signal Process. 50(10), 2563–2579 (2002). https://doi.org/10.1109/TSP.2002.803324
Sturm, B.L., Christensen, M.G.: Comparison of orthogonal matching pursuit implementations. In: Proc. 20th Eur. Signal Process. Conf. (EUSIPCO), pp. 220–224. IEEE (2012). https://doi.org/10.5281/zenodo.52420
Tropp, J.A., Gilbert, A.C.: Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans. Inf. Theory 53(12), 4655–4666 (2007). https://doi.org/10.1109/TIT.2007.909108
Xiao, M., Mumtaz, S., Huang, Y., et al.: Millimeter wave communications for future mobile networks. IEEE J. Sel. Areas Commun. 35(9), 1909–1935 (2017). https://doi.org/10.1109/JSAC.2017.2719924
Xie, T., Dai, L., Ng, D.W.K., Chae, C.B.: On the power leakage problem in millimeter-wave massive MIMO with lens antenna arrays. IEEE Trans. Signal Process. 67(18), 4730–4744 (2019). https://doi.org/10.1109/TSP.2019.2926019
Yang, L., Zeng, Y., Zhang, R.: Efficient channel estimation for millimeter wave MIMO with limited RF chains. Proc. IEEE Int. Conf. Commun. ICC, 1–6 (2016). https://doi.org/10.1109/ICC.2016.7510952
Zeng, Y., Zhang, R.: Millimeter wave MIMO with lens antenna array: a new path division multiplexing paradigm. IEEE Trans. Commun. 64(4), 1557–1571 (2016). https://doi.org/10.1109/TCOMM.2016.2533490
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Mehmet Ali Aygül and Mahmoud Nazzal performed computer-based simulations, wrote the paper, and developed the system model. The development of the manuscript was supervised by Hüseyin Arslan. All of the authors have read and approved the contents of this manuscript.
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The work of H. Arslan was supported in part by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant No. 5200030 with the cooperation of VESTEL and Istanbul Medipol University.
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Aygül, M.A., Nazzal, M. & Arslan, H. Using OMP and SD algorithms together in mm-Wave mMIMO channel estimation. SIViP 16, 1205–1213 (2022). https://doi.org/10.1007/s11760-021-02071-5
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DOI: https://doi.org/10.1007/s11760-021-02071-5