Abstract
Spatial multiplexing of multiple users, i.e., Multi User Multiple-Input Multiple-Output (MU-MIMO), is considered as a promising technique in multi-antenna broadcast systems to achieve high spectral efficiencies by serving multiple users in parallel over the same time-frequency resources Weingarten, Steinberg and Shamai, IEEE Trans. Inf. Theor. 52:3936–3964, 2006; Gesbert, Kountouris, Heath Jr., Chae, and Slzer, IEEE Signal Process. Mag. 24:36, 2007 [1, 2]. In contrast to Single User Multiple-Input Multiple-Output (SU-MIMO), the potential multiplexing gain of MU-MIMO is only confined by the capabilities of the transmitter. Hence, with MU-MIMO the need for multiple antennas at the users is eliminated, facilitating the development of small and cheap user equipments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
H. Weingarten, Y. Steinberg, S. Shamai, The capacity region of the Gaussian multiple-input multiple-output broadcast channel. IEEE Trans. Inf. Theor. 52(9), 3936–3964 (2006)
D. Gesbert, M. Kountouris, R. Heath Jr., C. Chae, T. Slzer, From single user to multiuser communications: shifting the MIMO paradigm. IEEE Signal Process. Mag. 24(5), 36 (2007)
D. Shiu, G. Foschini, M. Gans, J. Kahn, Fading correlation and its effect on the capacity of multielement antenna systems. IEEE Trans. Commun. 48(3), 502–513 (2000)
A. Molisch, A generic model for MIMO wireless propagation channels in macro- and microcells. IEEE Trans. Signal Process. 52(1), 61–71 (2004)
N. Jindal, MIMO broadcast channels with finite-rate feedback. IEEE Trans. Inf. Theor. 52(11), 5 (2006)
N. Ravindran, N. Jindal, Limited feedback-based block diagonalization for the MIMO broadcast channel. IEEE J. Sel. Areas Commun. 26(8), 1473–1482 (2008)
H. Bizaki, A. Falahati, Tomlinson-harashima precoding with imperfect channel state information. IET Commun. 2(1), 151–158 (2008)
D. Ryan, I. Collings, I.V.L. Clarkson, R. Heath Jr., Performance of vector perturbation multiuser MIMO systems with limited feedback. IEEE Trans. Commun. 57(9), 2633–2644 (2009)
A. Razi, D. Ryan, I. Collings, J. Yuan, Sum rates, rate allocation, and user scheduling for multi-user MIMO vector perturbation precoding. IEEE Trans. Wirel. Commun. 9(1), 356–365 (2010)
C. Peel, B. Hochwald, A. Swindlehurst, A vector-perturbation technique for near-capacity multiantenna multiuser communication-part I: channel inversion and regularization. IEEE Trans. Commun. 53(1), 195–202 (2005)
Q. Spencer, A. Swindlehurst, M. Haardt, Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels. IEEE Trans. Signal Process. 52(2), 461–471 (2004)
J.S. Kim, H. Kim, C.S. Park, K.B. Lee, On the performance of multiuser MIMO systems in WCDMA/HSDPA: beamforming, feedback and user diversity. IEICE Trans. 89, 2161–2169 (2006)
B. Mondal, S. Dutta, R. Heath Jr., Quantization on the Grassmann manifold. IEEE Trans. Signal Process. 55(8), 4208–4216 (2007)
W. Dai, Y. Liu, B. Rider, Quantization bounds on Grassmann manifolds and applications to MIMO communications. IEEE Trans. Inf. Theor. 54(3), 1108–1123 (2008)
J. Lee, N. Jindal, High SNR analysis for MIMO broadcast channels: dirty paper coding versus linear precoding. IEEE Trans. Inf. Theor. 53(12), 4787–4792 (2007)
V. Cadambe, S. Jafar, Interference alignment and degrees of freedom of the K-user interference channel. IEEE Trans. Inf. Theor. 54(8), 3425–3441 (2008)
M. Maddah-Ali, A. Motahari, A. Khandani, Communication over MIMO X channels: Interference alignment, decomposition, and performance analysis. IEEE Trans. Inform. Theor. 54(8), 3457–3470 (2008)
J. Park, B. Lee, B. Shim, A MMSE vector precoding with block diagonalization for multiuser MIMO downlink. IEEE Trans. Commun. 60(2), 569–577 (2012)
S. Schwarz, Limited feedback transceiver design for downlink MIMO OFDM cellular networks, Ph.D. Dissertation, Technische Universität Wien (2013). http://theses.eurasip.org/theses/514/limited-feedback-transceiver-design-for-downlink/
B. Nosrat-Makouei, J. Andrews, R. Heath Jr., MIMO interference alignment over correlated channels with imperfect CSI. IEEE Trans. Signal Process. 59(6), 2783–2794 (2011)
M. Rezaeekheirabadi, M. Guillaud, Limited feedback for interference alignment in the k-user MIMO interference channel, in Proceedings of the Information Theory Workshop (Lausanne, 2012), pp. 1–5
L. Qiang, Y. Yang, F. Shu, W. Gang, SLNR precoding based on QBC with limited feedback in downlink CoMP system," in International Conference on Wireless Communications and Signal Processing (2010), pp. 1–5
S. Schwarz, M. Rupp, Adaptive channel direction quantization for frequency selective channels, in 20th European Signal Processing Conference (Bucarest, 2012), pp. 2536–2540
T. Inoue, R. Heath, Jr., Grassmannian predictive frequency domain compression for limited feedback beamforming, in Information Theory and Applications Workshop (2010), pp. 173–177
D. Love, R. Heath Jr., Limited feedback unitary precoding for spatial multiplexing systems. IEEE Trans. Inf. Theor. 51(8), 2967–2976 (2005)
I.S. Dhillon, R. Heath Jr., T. Strohmer, J.A. Tropp, Constructing packings in Grassmannian manifolds via alternating projection, ArXiv e-prints (2007)
W. Santipach, M. Honig, Capacity of a multiple-antenna fading channel with a quantized precoding matrix. IEEE Trans. Inf. Theor. 55(3), 1218–1234 (2009)
D. Love, R. Heath Jr., Limited feedback diversity techniques for correlated channels. IEEE Trans. Veh. Tech. 55(2), 718–722 (2006)
S. Schwarz, R. Heath Jr., M. Rupp, Multiuser MIMO in distributed antenna systems with limited feedback, in IEEE 4th International Workshop on Heterogeneous and Small Cell Networks, GLOBECOM (Anaheim, 2012)
S. Schwarz, R. Heath Jr., M. Rupp, Single-user MIMO versus multi-user MIMO in distributed antenna systems with limited feedback. EURASIP J. Adv. Signal Process. 2013(54), 1–20 (2013)
B. Clerckx, G. Kim, S. Kim, MU-MIMO with channel statistics-based codebooks in spatially correlated channels, in IEEE Global Telecommunications Conference (2008) pp. 1–5
E. Park, H. Kim, H. Park, I. Lee, Feedback bit allocation schemes for multi-user distributed antenna systems. IEEE Commun. Lett. 17(1), 99–102 (2013)
A. Gersho, R. Gray, Vector Quantization and Signal Compression, The Kluwer international series in engineering and computer science : communications and information theory (Kluwer Academic Publishers, Boston, 1992)
B. Zhou, L. Jiang, S. Zhao, C. He, BER analysis of TDD downlink multiuser MIMO systems with imperfect channel state information. EURASIP J. Adv. Signal Process. 2011(1), 104 (2011)
D. McNamara, M. Beach, P. Fletcher, Experimental investigation of the temporal variation of MIMO channels, in IEEE 54th Vehicular Technology Conference, vol. 2 (2001), pp. 1063–1067
K. Baddour, N. Beaulieu, Autoregressive modeling for fading channel simulation. IEEE Trans. Wirel. Commun. 4(4), 1650–1662 (2005)
B. Hassibi, Random matrices, integrals and space-time systems, in DIMACS Workshop on Algebraic Coding Theory and Information Theory (Piscataway, 2003)
D. Maiwald, D. Kraus, Calculation of moments of complex Wishart and complex inverse Wishart distributed matrices. IEE Proc. Radar Sonar Navig. 147(4), 162–168 (2000)
S. Schwarz, R. Heath Jr., M. Rupp, Adaptive quantization on a Grassmann-manifold for limited feedback beamforming systems. IEEE Trans. Signal Process. 61(18), 4450–4462 (2013)
O. El Ayach, R. Heath Jr., Grassmannian differential limited feedback for interference alignment. IEEE Trans. Signal Process. 60(12), 6481–6494 (2012)
Y. Zhang, M. Lei, Robust Grassmannian prediction for limited feedback multiuser MIMO systems, in IEEE Wireless Communications and Networking Conference (2012), pp. 863–867
S. Schwarz, R. Heath, Jr., M. Rupp, Adaptive quantization on the Grassmann-manifold for limited feedback multi-user MIMO systems, in 38th International Conference on Acoustics, Speech and Signal Processing (Vancouver, 2013)
S. Haykin, Adaptive filter theory, 4th edn. (Prentice Hall, New Jersey, 2002)
R.H. Clarke, A statistical theory of mobile radio reception. Bell Syst. Tech. J. 47, 957–1000 (1968)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this chapter
Cite this chapter
Rupp, M., Schwarz, S., Taranetz, M. (2016). Multi User and Multi Cell Simulations. In: The Vienna LTE-Advanced Simulators. Signals and Communication Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-0617-3_6
Download citation
DOI: https://doi.org/10.1007/978-981-10-0617-3_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0616-6
Online ISBN: 978-981-10-0617-3
eBook Packages: EngineeringEngineering (R0)