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Limited Feedback Precoding for Massive MIMO

DOI: 10.1155/2013/416352

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The large-scale array antenna system with numerous low-power antennas deployed at the base station, also known as massive multiple-input multiple-output (MIMO), can provide a plethora of advantages over the classical array antenna system. Precoding is important to exploit massive MIMO performance, and codebook design is crucial due to the limited feedback channel. In this paper, we propose a new avenue of codebook design based on a Kronecker-type approximation of the array correlation structure for the uniform rectangular antenna array, which is preferable for the antenna deployment of massive MIMO. Although the feedback overhead is quite limited, the codebook design can provide an effective solution to support multiple users in different scenarios. Simulation results demonstrate that our proposed codebook outperforms the previously known codebooks remarkably. 1. Introduction High-rate data demand increases faster and faster with the new generation of devices (smart phones, tablets, netbooks, etc.). However, the huge increase in demand can be hardly met by current wireless systems. As is known to us, MIMO channels, created by deploying antenna arrays at the transmitter and receiver, promise high-capacity and high-quality wireless communication links by spatial multiplexing and diversity. Basically, the more antennas the transmitter or the receiver equipped with, the more degrees of freedom that the propagation channel can provide, and the higher data rate the system can offer. Therefore, there is significant effort within the community to research and develop massive MIMO technology, which is a hot topic nowadays [1]. For multiuser MIMO systems, we can utilize precoding to explore massive MIMO potentials. The essence of precoding techniques is to mitigate the interuser interference and to improve the effective received SNR. Herein, channel state information at the transmitter (CSIT) is an essential component when trying to maximize massive MIMO performance via precoding. In time division duplexing (TDD) system, channel reciprocity can be utilized for pilot training in the uplink to acquire the complete CSIT, but the pilot contamination and imperfect channel estimation based on uplink pilots would lead to inaccuracy of the CSIT. In frequency division duplexing (FDD) system, the CSIT shall be acquired via the feedback channel, which is usually limited in practice. Hence, a finite set of precoding matrices, named codebook, known to both the receiver and the transmitter should be predesigned. The receiver selects the optimal precoding matrix from the

References

[1]  F. Rusek, D. Persson, B. K. Lau et al., “Scaling up MIMO: opportunities and challenges with very large arrays,” IEEE Signal Processing Magazine, vol. 30, no. 1, pp. 40–60, 2013.
[2]  E. Visotsky and U. Madhow, “Space-time transmit precoding with imperfect feedback,” IEEE Transactions on Information Theory, vol. 47, no. 6, pp. 2632–2639, 2001.
[3]  T. Inoue and R. W. Heath Jr., “Kerdock codes for limited feedback precoded MIMO systems,” IEEE Transactions on Signal Processing, vol. 57, no. 9, pp. 3711–3716, 2009.
[4]  J. C. Roh and B. D. Rao, “Design and analysis of MIMO spatial multiplexing systems with quantized feedback,” IEEE Transactions on Signal Processing, vol. 54, no. 8, pp. 2874–2886, 2006.
[5]  D. J. Love and R. W. Heath Jr., “Limited feedback unitary precoding for spatial multiplexing systems,” IEEE Transactions on Information Theory, vol. 51, no. 8, pp. 2967–2976, 2005.
[6]  K. Schober, R. Wichman, and T. Koivisto, “MIMO adaptive codebook for closely spaced antenna arrays,” in Proceedings of the European Signal Processing Conference (EUSIPCO '11), pp. 1–5, Barcelona, Spain, August 2011.
[7]  D. J. Ryan, I. V. L. Clarkson, I. B. Collings, D. Guo, and M. L. Honig, “QAM codebooks for low-complexity limited feedback MIMO beamforming,” in Proceedings of the IEEE International Conference on Communications (ICC '07), pp. 4162–4167, June 2007.
[8]  A. L. Moustakas, H. U. Baranger, L. Balents, A. M. Sengupta, and S. H. Simon, “Communication through a diffusive medium: coherence and capacity,” Science, vol. 287, no. 5451, pp. 287–290, 2000.
[9]  T. Shuang, T. Koivisto, H.-L. M??tt?nen, K. Pietik?inen, T. Roman, and M. Enescu, “Design and evaluation of LTE-Advanced double codebook,” in Proceedings of the IEEE 73rd Vehicular Technology Conference (VTC '11), pp. 1–5, Yokohama, Japan, May 2011.
[10]  A. M. Sayeed, “Deconstructing multiantenna fading channels,” IEEE Transactions on Signal Processing, vol. 50, no. 10, pp. 2563–2579, 2002.
[11]  K. Amiri, D. Shamsi, B. Aazhang, and J. R. Cavallaro, “Adaptive codebook for beamforming in limited feedback MIMO systems,” in Proceedings of the 42nd Annual Conference on Information Sciences and Systems (CISS '08), pp. 994–998, March 2008.
[12]  G. Levin and S. Loyka, “On capacity-maximizing angular densities of multipath in MIMO channels,” in Proceedings of the 72nd Vehicular Technology Conference Fall (VTC '10), Ottawa, Canada, September 2010.
[13]  C. F. V. Loan, “The ubiquitous Kronecker product,” Journal of Computational and Applied Mathematics, vol. 123, no. 1-2, pp. 85–100, 2000.
[14]  A. Paulraj, R. Nabar, and D. Gore, Introduction To Space-Time Wireless Communications, Cambridge University Press, Cambridge, UK, 2003.
[15]  X. Gao, O. Edfors, F. Rusek, and F. Tufvesson, “Linear pre-coding performance in measured very-large MIMO channels,” in Proceedings of the 74th Vehicular Technology Conference (VTC '11), San Francisco, Calif, USA, September 2011.
[16]  Rec. ITU-R M. 1225, guidelines for evaluation of radio transmission technologies for IMT-2000, 1998.
[17]  J. C. Roh and B. D. Rao, “Design and analysis of MIMO spatial multiplexing systems with quantized feedback,” IEEE Transactions on Signal Processing, vol. 54, no. 8, pp. 2874–2886, 2006.
[18]  “IST-WINNER II Deliverable 1. 1. 2 v. 1. 2. WINNER II Channel Models, IST-WINNER2,” Tech. Rep., 2007, http://www.ist-winner.org/deliverables.html.
[19]  “Evolved Universal Terrestrial Radio Access (E-UTRA), Physical layer procedures,” 3GPP TS 36. 213 V10. 6. 0, 2012.
[20]  E. Jorswieck, A. Sezgin, B. Ottersten, and A. Paulraj, “Feedback reduction in uplink MIMO OFDM systems by chunk optimization,” Eurasip Journal on Advances in Signal Processing, vol. 2008, Article ID 597072, pp. 1–14, 2008.

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