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Journal of applied research and technology
versión On-line ISSN 2448-6736versión impresa ISSN 1665-6423
J. appl. res. technol vol.9 no.3 Ciudad de México dic. 2011
Improved Iterative Coordinated Beamforming Based on Singular Value Decomposition for Multiuser Mimo Systems With Limited Feedforward
L. SorianoEquigua*1, J. SánchezGarcía2, C.B. Chae3, R. W. Heath Jr.4
1,2 Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Carretera EnsenadaTijuana No. 3918, Zona Playitas, Ensenada, B. C. México. C.P. 22860. *Email: lsoriano@cicese.mx
3 School of Integrated Technology, College of Engineering, Yonsei University, 1621 Songdodong, Yeonsugu, Incheon, 406840, Korea
4 Wireless Networking and Communications Group (WNCG), Department of Electrical and Computer Engineering, The University of Texas at Austin, 1 University Station C0803, Austin, TX, USA 78712.
ABSTRACT
Coordinated beamforming based on singular value decomposition is an iterative method to jointly optimize the transmit beamformers and receive combiners, to achieve high levels of sum rates in the downlink of multiuser systems, by exploiting the multidimensional wireless channel created by multiple transmit and receive antennas. The optimization is done at the base station and the quantized beamformers are sent to the users through a low rate link. In this work, we propose to optimize this algorithm by reducing the number of iterations and improving its uncoded bit error rate performance. Simulation results show that our proposal achieves a better bit error rate with a lower number of iterations than the original algorithm.
Keywords: Coordinated beamforming, multiuser MIMO, iterative, convergence, bit error rate.
RESUMEN
El beamforming coordinado basado en descomposición de matrices en valores singulares, es un método iterativo que nos permite calcular conjuntamente los vectores de peso de las antenas transmisoras en la estación base y las antenas receptoras en los móviles, para alcanzar altos niveles de tasas de bits en el canal de bajada de sistemas MIMO multiusuario. La optimización se realiza en la estación base y los vectores de peso cuantizados del transmisor se envían a cada usuario a través de un enlace de baja velocidad. En este trabajo, nosotros proponemos optimizar este algoritmo para reducir el número de iteraciones necesarias para que el algoritmo converja y mejorar la tasa de bit errónea. Los resultados de las simulaciones realizadas muestran que nuestra propuesta alcanza una mejor tasa de bit errónea con un menor número de iteraciones.
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Acknowledgements
The work of C.B. Chae was in part supported by the Ministry of Knowledge Economy under the "IT Consilience Creative Program" (NIPA2010C151510010001).
References
[1] Telatar I. E., Capacity of multiantenna Gaussian channels, European Transactions on Telecommunications, Nov. 1999, vol. 10, no. 6, pp. 585595. [ Links ]
[2] Foschini G. J. and Gans M. J., On limits of wireless communications in a fading environment when using multiple antennas, Wireless Networks Communications, Mar. 1998, vol. 6 no. 3, pp 311335. [ Links ]
[3] Gesbert D., Shafi M., Shiu D.S., Smith P. J., and Naguib A., From theory to practice: an overview of MIMO spacetime coded wireless sytems, IEEE Journal on Selected Areas in Communications, Apr. 2003, vol. 21, no. 3, pp. 281302. [ Links ]
[4] Spencer Q. H., Peel C. B., Swindlehurst A. L., and Haardt M., An introduction to the multiuser MIMO downlink, IEEE Communications Magazine, Oct. 2004, vol. 42, no. 10, pp. 6067. [ Links ]
[5] Zhang C., Xu W., Chen M. Hybrid zeroforcing beamforming/orthogonal beamforming with user selection for MIMO broadcast channels, IEEE Communications Letters, Jan. 2009, vol. 13, no. 1, pp. 1012. [ Links ]
[6] Peel C. B., Hochwald B. M., Swindlehurst A. L., A vectorperturbation technique for nearcapacity multiantenna multiuser communicationpart I: Channel inversion and regularization, IEEE Transactions on Communications, Jan. 2005, vol. 53, no. 1, pp. 195202. [ Links ]
[7] FarhangBoroujeny B., Spencer Q., and Swindlehurst A. L., Layering techniques for spacetime communications in multiuser networks, in Proc. of IEEE Vehicular Technology Conference, Oct. 2003, vol. 2, pp. 13391342. [ Links ]
[8] Choi L. and Murch R.D., A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach, IEEE Transactions on Wireless Communications, vol. 3, no. 1, Jan. 2004, pp. 2024. [ Links ]
[9] Pan Z., Wong K.K., and Ng T.S., Generalized multiuser orthogonal spacedivision multiplexing, IEEE Transactions on Wireless Communications, vol. 3, Nov. 2004, pp. 19691973. [ Links ]
[10] Chae C.B., Mazzarese D., and Heath R. W. Jr., Coordinated beamforming for multiuser mimo systems with limited feedforward. Proc. of IEEE Asilomar Conference on Signals, Systems, and Computers, 2006, pages 15111515, Pacific Grove, CA, Oct. [ Links ]
[11] Chae C.B., Mazzarese D., Inoue T., and Heath R. W. Jr., Coordinated beamforming for the multiuser MIMO broadcast channel with limited feedforward. IEEE Transactions on Signal Processing, Dec. 2008, vol. 56, no. 12, pp. 60446056. [ Links ]
[12] Kim E.Y., Chun J. Coordinated beamforming with reduced overhead for the downlink of multiuser MIMO systems. IEEE Communication Letters, Nov. 2008, vol. 2, no. 11, pp. 810 812. [ Links ]
[13] Love D. J., Heath R. W. Jr., and Strohmer T., Grassmannian beamforming for multipleinput multipleoutput wireless systems, IEEE Transactions on Information Theory, vol. 49, Oct. 2003, pp. 27352747. [ Links ]
[14] Horn R. A. and Johnson C. R., Matrix analysis, 1st Ed., Cambridge university press, 1985, pp. 259262. [ Links ]
[15] Scharnhorst K., Angles in Complex Vector Spaces, Acta Applicandae Mathematicae, Vol. 69, No. 1, October, 2001, pp. 95103. [ Links ]