Active channel sparsification: realizing frequency-division duplexing massive MIMO with minimal overhead. (English) Zbl 1504.94045
Kutyniok, Gitta (ed.) et al., Compressed sensing in information processing. Cham: Birkhäuser. Appl. Numer. Harmon. Anal., 337-367 (2022).
Summary: Multiuser multiple-input multiple-output (MIMO) consists of exploiting multiple antennas at the base station (BS) side, in order to multiplex over the spatial-domain several data streams to a number of users sharing the same time-frequency transmission resource (channel bandwidth and time slots).
For the entire collection see [Zbl 1497.94001].
For the entire collection see [Zbl 1497.94001].
MSC:
| 94A12 | Signal theory (characterization, reconstruction, filtering, etc.) |
| 94A40 | Channel models (including quantum) in information and communication theory |
Software:
MatlabReferences:
| [1] | Adhikary, A.; Nam, J.; Ahn, JY; Caire, G., Joint spatial division and multiplexing: the large-scale array regime, IEEE Trans. Inf. Theory, 59, 10, 6441-6463 (2013) · Zbl 1364.94016 · doi:10.1109/TIT.2013.2269476 |
| [2] | Ali, A.; González-Prelcic, N.; Heath, RW, Millimeter wave beam-selection using out-of-band spatial information, IEEE Trans. Wirel. Commun., 17, 2, 1038-1052 (2017) · doi:10.1109/TWC.2017.2773532 |
| [3] | Bajwa, WU; Haupt, J.; Sayeed, AM; Nowak, R., Compressed channel sensing: A new approach to estimating sparse multipath channels, Proc. IEEE, 98, 6, 1058-1076 (2010) · doi:10.1109/JPROC.2010.2042415 |
| [4] | Bertsekas, D.P., Scientific, A.: Convex optimization algorithms. In: Athena Scientific Belmont (2015) · Zbl 1347.90001 |
| [5] | Boccardi, F.; Heath, RW; Lozano, A.; Marzetta, TL; Popovski, P., Five disruptive technology directions for 5G, IEEE Commun. Mag., 52, 2, 74-80 (2014) · doi:10.1109/MCOM.2014.6736746 |
| [6] | Caire, G., On the ergodic rate lower bounds with applications to massive MIMO, IEEE Trans. Wirel. Commun., 17, 5, 3258-3268 (2018) · doi:10.1109/TWC.2018.2808522 |
| [7] | Caire, G.; Jindal, N.; Kobayashi, M.; Ravindran, N., Multiuser MIMO achievable rates with downlink training and channel state feedback, IEEE Trans. Inf. Theory, 56, 6, 2845-2866 (2010) · Zbl 1366.94226 · doi:10.1109/TIT.2010.2046225 |
| [8] | Candès, EJ; Wakin, MB, An introduction to compressive sampling, IEEE Signal Process. Mag., 25, 2, 21-30 (2008) · doi:10.1109/MSP.2007.914731 |
| [9] | Chan, PW; Lo, ES; Wang, RR; Au, EK; Lau, VK; Cheng, RS; Mow, WH; Murch, RD; Letaief, KB, The evolution path of 4G networks: FDD or TDD?, IEEE Commun. Mag., 44, 12, 42-50 (2006) · doi:10.1109/MCOM.2006.273098 |
| [10] | Chen, J.; Huo, X., Theoretical results on sparse representations of multiple-measurement vectors, IEEE Trans. Signal Process., 54, 12, 4634-4643 (2006) · Zbl 1375.94051 · doi:10.1109/TSP.2006.881263 |
| [11] | Dai, J.; Liu, A.; Lau, VK, FDD massive MIMO channel estimation with arbitrary 2d-array geometry, IEEE Trans. Signal Process., 66, 10, 2584-2599 (2018) · Zbl 1415.94086 · doi:10.1109/TSP.2018.2807390 |
| [12] | Davoodi, AG; Jafar, SA, Aligned image sets under channel uncertainty: Settling conjectures on the collapse of degrees of freedom under finite precision CSIT, IEEE Trans. Inf. Theory, 62, 10, 5603-5618 (2016) · Zbl 1359.94031 · doi:10.1109/TIT.2016.2586918 |
| [13] | Decurninge, A., Guillaud, M., Slock, D.T.: Channel covariance estimation in massive MIMO frequency division duplex systems. In: Proceedings of the 2015 IEEE Globecom Workshops (GC Wkshps), pp. 1-6. IEEE, New York (2015) |
| [14] | Dimic, G., Sidiropoulos, n.d.: On downlink beamforming with greedy user selection: performance analysis and a simple new algorithm. IEEE Trans. Signal Process. 53(10), 3857-3868 (2005) · Zbl 1370.94104 |
| [15] | Ding, Y.; Rao, BD, Dictionary learning-based sparse channel representation and estimation for FDD massive MIMO systems, IEEE Trans. Wirel. Commun., 17, 8, 5437-5451 (2018) · doi:10.1109/TWC.2018.2843786 |
| [16] | Donoho, DL, Compressed sensing, IEEE Trans. Inf. Theory, 52, 4, 1289-1306 (2006) · Zbl 1288.94016 · doi:10.1109/TIT.2006.871582 |
| [17] | Eldar, YC; Rauhut, H., Average case analysis of multichannel sparse recovery using convex relaxation, IEEE Trans. Inf. Theory, 56, 1, 505-519 (2010) · Zbl 1366.94095 · doi:10.1109/TIT.2009.2034789 |
| [18] | Gao, X., Edfors, O., Rusek, F., Tufvesson, F.: Linear pre-coding performance in measured very-large MIMO channels. In: Proceedings of the 2011 IEEE Vehicular Technology Conference (VTC Fall), pp. 1-5. IEEE, New York (2011) |
| [19] | Gao, Z.; Dai, L.; Wang, Z.; Chen, S., Spatially common sparsity based adaptive channel estimation and feedback for FDD massive MIMO, IEEE Trans. Signal Process., 63, 23, 6169-6183 (2015) · Zbl 1395.94109 · doi:10.1109/TSP.2015.2463260 |
| [20] | Gray, R.M.: Toeplitz and circulant matrices: A review. Foundations and TrendsⓇin Communications and Information Theory 2(3), 155-239 (2006). Now publishers inc · Zbl 1115.15021 |
| [21] | Grimmett, GS, Probability and random processes (2020), Oxford: Oxford University Press, Oxford · Zbl 1437.60004 |
| [22] | Haghighatshoar, S., Khalilsarai, M.B., Caire, G.: Multi-band covariance interpolation with applications in massive MIMO. In: 2018 IEEE International Symposium on Information Theory (ISIT), pp. 386-390. IEEE, New York (2018) |
| [23] | Horn, RA; Johnson, CR, Matrix analysis (1990), Cambridge: Cambridge University Press, Cambridge · Zbl 0704.15002 |
| [24] | Hoydis, J., Hoek, C., Wild, T., ten Brink, S.: Channel measurements for large antenna arrays. In: Proceedings of the 2012 International Symposium on Wireless Communication Systems (ISWCS), pp. 811-815. IEEE, New York (2012) |
| [25] | Hugl, K., Kalliola, K., Laurila, J.: Spatial reciprocity of uplink and downlink radio channels in FDD systems. Proc. COST 273 Technical Document TD (02) 66, 7 (2002) |
| [26] | Jiang, Z.; Molisch, AF; Caire, G.; Niu, Z., Achievable rates of FDD massive MIMO systems with spatial channel correlation, IEEE Trans. Wirel. Commun., 14, 5, 2868-2882 (2015) · doi:10.1109/TWC.2015.2396058 |
| [27] | Jindal, N., MIMO broadcast channels with finite-rate feedback, IEEE Trans. Inf. Theory, 52, 11, 5045-5060 (2006) · Zbl 1320.94051 · doi:10.1109/TIT.2006.883550 |
| [28] | Kaltenberger, F., Gesbert, D., Knopp, R., Kountouris, M.: Correlation and capacity of measured multi-user MIMO channels. In: IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, 2008 (PIMRC 2008), pp. 1-5. IEEE, New York (2008) |
| [29] | Khalilsarai, MB; Haghighatshoar, S.; Yi, X.; Caire, G., FDD massive MIMO via UL/DL channel covariance extrapolation and active channel sparsification, IEEE Trans. Wirel. Commun., 18, 1, 121-135 (2018) · doi:10.1109/TWC.2018.2877684 |
| [30] | Khalilsarai, M.B., Haghighatshoar, S., Caire, G.: Joint approximate covariance diagonalization with applications in MIMO virtual beam design. In: 2020 IEEE Global Communications Conference (GLOBECOM). IEEE, New York (2020) |
| [31] | Klebaner, FC, Introduction to stochastic calculus with applications (2005), Singapore: World Scientific, Singapore · Zbl 1077.60001 · doi:10.1142/p386 |
| [32] | Kobayashi, M.; Jindal, N.; Caire, G., Training and feedback optimization for multiuser MIMO downlink, IEEE Trans. Commun., 59, 8, 2228-2240 (2011) · doi:10.1109/TCOMM.2011.051711.090752 |
| [33] | Kyritsi, P.; Cox, DC; Valenzuela, RA; Wolniansky, PW, Correlation analysis based on MIMO channel measurements in an indoor environment, IEEE J. Sel. Areas Commun., 21, 5, 713-720 (2003) · doi:10.1109/JSAC.2003.810299 |
| [34] | Larsson, EG; Edfors, O.; Tufvesson, F.; Marzetta, TL, Massive MIMO for next generation wireless systems, IEEE Commun. Mag., 52, 2, 186-195 (2014) · doi:10.1109/MCOM.2014.6736761 |
| [35] | Love, DJ; Heath, RW; Strohmer, T., Grassmannian beamforming for multiple-input multiple-output wireless systems, IEEE Trans. Inf. Theory, 49, 10, 2735-2747 (2003) · Zbl 1301.94080 · doi:10.1109/TIT.2003.817466 |
| [36] | Lozano, A.; Heath, RW; Andrews, JG, Fundamental limits of cooperation, IEEE Trans. Inf. Theory, 59, 9, 5213-5226 (2013) · Zbl 1364.94047 · doi:10.1109/TIT.2013.2253153 |
| [37] | Malkowsky, S.; Vieira, J.; Liu, L.; Harris, P.; Nieman, K.; Kundargi, N.; Wong, IC; Tufvesson, F.; Öwall, V.; Edfors, O., The world’s first real-time testbed for massive MIMO: Design, implementation, and validation, IEEE Access, 5, 9073-9088 (2017) · doi:10.1109/ACCESS.2017.2705561 |
| [38] | Manton, JH, Optimization algorithms exploiting unitary constraints, IEEE Trans. Signal Process., 50, 3, 635-650 (2002) · Zbl 1369.90169 · doi:10.1109/78.984753 |
| [39] | Marzetta, T.L.: How much training is required for multiuser MIMO? In: Fortieth Asilomar Conference on Signals, Systems and Computers, 2006 (ACSSC’06), pp. 359-363. IEEE, New York (2006) |
| [40] | Marzetta, TL, Noncooperative cellular wireless with unlimited numbers of base station antennas, IEEE Trans. Wireless Commun., 9, 11, 3590-3600 (2010) · doi:10.1109/TWC.2010.092810.091092 |
| [41] | Marzetta, TL; Larsson, EG; Yang, H.; Ngo, HQ, Fundamentals of Massive MIMO (2016), Cambridge: Cambridge University, Cambridge · doi:10.1017/CBO9781316799895 |
| [42] | MATLAB: version 9.9.0 (R2010b). The MathWorks Inc., Natick, Massachusetts (2020) |
| [43] | Miretti, L., Cavalcante, R.L.G., Stanczak, S.: FDD massive MIMO channel spatial covariance conversion using projection methods. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3609-3613. IEEE, New York (2018) |
| [44] | Nam, J., Adhikary, A., Ahn, J.Y., Caire, G.: Joint spatial division and multiplexing: Opportunistic beamforming, user grouping and simplified downlink scheduling. IEEE J. Sel. Top. Sign. Proces. (JSTSP) 8(5), 876-890 (2014) |
| [45] | Pascual-García, J.; Molina-García-Pardo, JM; Martinez-Ingles, MT; Rodriguez, JV; Saurin-Serrano, N., On the importance of diffuse scattering model parameterization in indoor wireless channels at mm-wave frequencies, IEEE Access, 4, 688-701 (2016) · doi:10.1109/ACCESS.2016.2526600 |
| [46] | Peajcariaac, JE; Tong, YL, Convex functions, partial orderings, and statistical applications (1992), London: Academic Press, London · Zbl 0749.26004 |
| [47] | Rao, X.; Lau, VK, Distributed compressive CSIT estimation and feedback for FDD multi-user massive MIMO systems, IEEE Trans. Signal Process., 62, 12, 3261-3271 (2014) · Zbl 1394.94473 · doi:10.1109/TSP.2014.2324991 |
| [48] | Rayal, F.: LTE in a Nutshell: The physical layer. In: Telesystem Innovations (2010) |
| [49] | Richter, A.: Estimation of Radio Channel Parameters: Models and Algorithms. ISLE, Blacksburg (2005) |
| [50] | Richter, A., Thomä, R.S.: Parametric modeling and estimation of distributed diffuse scattering components of radio channels (2003) |
| [51] | Sánchez-Fernández, M.; Jamali, V.; Llorca, J.; Tulino, A., Gridless multidimensional angle of arrival estimation for arbitrary 3D antenna arrays, IEEE Trans. Wirel. Commun., 20, 7, 4748-4764 (2021) · doi:10.1109/TWC.2021.3062558 |
| [52] | Sayeed, AM, Deconstructing multiantenna fading channels, IEEE Trans. Signal Process., 50, 10, 2563-2579 (2002) · doi:10.1109/TSP.2002.803324 |
| [53] | Sesia, S.; Toufik, I.; Baker, M., LTE-the UMTS long term evolution: from theory to practice (2011), New York: Wiley, New York · doi:10.1002/9780470978504 |
| [54] | Sim, MS; Park, J.; Chae, CB; Heath, RW, Compressed channel feedback for correlated massive MIMO systems, J. Commun. Networks, 18, 1, 95-104 (2016) · doi:10.1109/JCN.2016.000012 |
| [55] | Thomä, R., Landmann, M., Richter, A., Trautwein, U.: Multidimensional high-resolution channel sounding. In: Smart Antennas in Europe-State-of-the-Art, vol. 3. Hindawi Publishing Corporation, London (2005) |
| [56] | Tse, D.; Viswanath, P., Fundamentals of wireless communication (2005), Cambridge: Cambridge University, Cambridge · Zbl 1099.94006 · doi:10.1017/CBO9780511807213 |
| [57] | Xie, H.; Gao, F.; Zhang, S.; Jin, S., A unified transmission strategy for TDD/FDD massive MIMO systems with spatial basis expansion model, IEEE Trans. Veh. Technol., 66, 4, 3170-3184 (2017) · doi:10.1109/TVT.2016.2594706 |
| [58] | Xie, H.; Gao, F.; Jin, S.; Fang, J.; Liang, YC, Channel estimation for TDD/FDD massive MIMO systems with channel covariance computing, IEEE Trans. Wirel. Commun., 17, 6, 4206-4218 (2018) · doi:10.1109/TWC.2018.2821667 |
| [59] | Yang, H.; Marzetta, TL, Performance of conjugate and zero-forcing beamforming in large-scale antenna systems, IEEE J. Sel. Areas Commun., 31, 2, 172-179 (2013) · doi:10.1109/JSAC.2013.130206 |
| [60] | Yin, H.; Gesbert, D.; Filippou, M.; Liu, Y., A coordinated approach to channel estimation in large-scale multiple-antenna systems, IEEE J. Sel. Areas Commun., 31, 2, 264-273 (2013) · doi:10.1109/JSAC.2013.130214 |
| [61] | Zheng, L.; Tse, DNC, Communication on the Grassmann manifold: A geometric approach to the noncoherent multiple-antenna channel, IEEE Trans. Inf. Theory, 48, 2, 359-383 (2002) · Zbl 1071.94503 · doi:10.1109/18.978730 |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
