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Fundamentals of Multi-User MIMO Communications

  • Luca Sanguinetti
  • H. Vincent Poor
Chapter

In recent years, the remarkable promise of multiple-antenna techniques has motivated an intense research activity devoted to characterizing the theoretical and practical issues associated with multiple-input multiple-output wireless channels. This activity was first focused primarily on single-user communications but more recently there has been extensive work on multi-user settings. The aim of this chapter is to provide an overview of the fundamental information-theoretic results and practical implementation issues of multi-user multiple-antenna networks operating under various conditions of channel state information.

Keywords

Channel State Information Broadcast Channel Ergodic Capacity Perfect Channel State Information Limited Feedback 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Biglieri, E., Proakis, J., and Shamai (Shitz), S. (1998) Fading channels: Information-theoretic and communications aspects. IEEE Transactions on Information Theory, vol. 44 (6) pp.2619–2692.MATHCrossRefGoogle Scholar
  2. 2.
    Ahslwede, R. (1971) Multi-way communication channels. In Proceedings of the IEEE International Symposium on Information Theory (Tsahkadsor, Armenian S.S.R.), Budapest, Hungary: Akademiai Kiado, June, pp. 23–52.Google Scholar
  3. 3.
    Cover, T., (1972) Broadcast channels. IEEE Transactions on Information Theory, vol. 18 (1) pp. 2–14.MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Cover, T. M., and Thomas, J. A. (1991) Elements of Information Theory. New York: Wiley-Interscience.MATHCrossRefGoogle Scholar
  5. 5.
    Tse, D., and Viswanath, P. (2005) Fundamentals of Wireless Communications. Cambridge, UK: Cambridge University Press.Google Scholar
  6. 6.
    Rimoldi, R., and Urbanke, R. (1996) A rate-splitting approach to the Gaussian multiple-access channel. IEEE Transactions on Information Theory, vol. 46 (2) pp. 364–375.CrossRefGoogle Scholar
  7. 7.
    Tse, D., and Hanly, S. V. (1998) Multiaccess fading channels – Part I : Polymatroid structure, optimal resource allocation and throughput capacities. IEEE Transactions on Information Theory, vol. 44 (7) pp. 2796–2815.MATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Boyd, S., and Vanderbenghe, L. (2003) Convex Optimization. Cambridge, UK: Cambridge University Press.Google Scholar
  9. 9.
    Cheng, R., and Verdú, S. (1993) Gaussian multiaccess channels with ISI: Capacity region and multiuser water-filling. IEEE Transactions on Information Theory, vol. 21 (5) pp. 684–702.Google Scholar
  10. 10.
    Vandenberghe, L., Boyd, S., and Wu, S. P. (1998) Determinant maximization with linear matrix inequality constraints. SIAM Journal Matrix Analytical Applications, vol. 19 (2) pp. 499–533.MATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Yu, W., Rhee, W., Boyd, S., and Cioffi, J. M. (2004) Iterative water-filling for Gaussian vector multiple-access channels. IEEE Transactions on Information Theory, vol. 50 (1) pp. 145–152.CrossRefMathSciNetGoogle Scholar
  12. 12.
    Yu, W., Rhee, W., and Cioffi, J. M. (2001) Optimal power control in multiple-access fading channels with multiple antennas. In Proceedings of IEEE International Conference on Communications, Helsinki, Finland, June 11–14, pp. 575–579.Google Scholar
  13. 13.
    Telatar, E. (1999) Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, vol. 10 (6) pp. 585–595.CrossRefGoogle Scholar
  14. 14.
    Rhee, W., and Cioffi, J. M. (2003) On the capacity of multi-user wireless channels with multiple antennas. IEEE Transactions on Information Theory, vol. 49 (10) pp. 2580–2595.CrossRefMathSciNetGoogle Scholar
  15. 15.
    Viswanath, P., Tse, D., and Anantharam, V. (2001) Asymptotically optimal water-filling in vector multiple-access channels. IEEE Transactions on Information Theory, vol. 47 (1) pp. 241–267.MATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Goldsmith, A., Jafar, S. A., Jindal, N., and Vishwanath, S. (2003) Capacity limits of MIMO channels. IEEE Journal on Selected Areas in Communications, vol. 21 (5) pp. 684–702.CrossRefGoogle Scholar
  17. 17.
    Viswanath, P., Tse, D., and Laroia, R. (2002) Opportunistic beamforming using dumb antennas. IEEE Transactions on Information Theory, vol. 48 (6) pp. 1277–1294.MATHCrossRefMathSciNetGoogle Scholar
  18. 18.
    Foschini, G. J. and Gans, M. J. (1998) On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Communications, vol. 6 (2) pp. 331–320.Google Scholar
  19. 19.
    Marton, K. (1979) A coding theorem for the discrete memoryless broadcast channel. IEEE Transactions on Information Theory, vol. 23 (3) pp. 306–311.CrossRefMathSciNetGoogle Scholar
  20. 20.
    Bergman, P. (1973) Random coding theorem for broadcast channels with degraded components. IEEE Transactions on Information Theory, vol. 19 (3), pp. 197–207.CrossRefGoogle Scholar
  21. 21.
    Weingarten, H., Steinberg, Y., and Shamai (Shitz), S. (2006) The capacity region of the Gaussian multiple-input multiple-output broadcast channel. IEEE Transactions on Information Theory, vol. 50 (9) pp. 3936–3964.CrossRefGoogle Scholar
  22. 22.
    Costa, M. (1983) Writing on dirty paper. IEEE Transactions on Information Theory, vol. 29 (3) pp. 439–441.MATHCrossRefGoogle Scholar
  23. 23.
    Yu, W., Sutivong, A., Julian, D., Cover, T. M., and Chiang, M. (2001) Writing on colored paper. In Proceedings of IEEE International Symposium on Information Theory, Washington, DC, USA, June 24–29, pp. 302–311.Google Scholar
  24. 24.
    Jindal, N., Vishwanath, S., and Goldsmith, A. (2004) On the duality of Gaussian multiple-access and broadcast channels. IEEE Transactions on Information Theory, vol. 50 (5) pp. 768–783.CrossRefMathSciNetGoogle Scholar
  25. 25.
    Viswanath, P., and Tse, D. (2003) Sum capacity of the vector Gaussian channel and uplink-downlink duality. IEEE Transactions on Information Theory, vol. 49 (8) pp. 1912–1921.CrossRefMathSciNetGoogle Scholar
  26. 26.
    Vishwanath, S., Jindal, N., and Goldsmith, A. (2003) Duality, achievable rates and sum rate capacity of Gaussian MIMO broadcast channels. IEEE Transactions on Information Theory, vol. 49 (10) pp. 2658–2668.CrossRefMathSciNetGoogle Scholar
  27. 27.
    Caire, G., and Shamai (Shitz), S. (2003) On the achievable throughput of a multiantenna Gaussian broadcast channel. IEEE Transactions on Information Theory, vol. 49 (7) pp. 1691–1706.CrossRefGoogle Scholar
  28. 28.
    Sato, H. (1978) An outer bound on the capacity region of broadcast channels. IEEE Transactions on Information Theory, vol. 24 (3) pp. 374–377.MATHCrossRefGoogle Scholar
  29. 29.
    Yu, W., and Cioffi, J. M. (2004) Sum capacity of the vector Gaussian channels. IEEE Transactions on Information Theory, vol. 50 (9) pp. 1875–1892.CrossRefMathSciNetGoogle Scholar
  30. 30.
    Jindal, N., Rhee, W., Vishwanath, S., Jafar, S. A., and Goldsmith, A. (2005) Sum power iterative water-filling for multi-antenna Gaussian broadcast channels. IEEE Transactions on Information Theory, vol. 51 (4) pp. 1570–1580.CrossRefMathSciNetGoogle Scholar
  31. 31.
    Yu, W., and Rhee, W. (2006) Degrees of freedom in wireless multiuser spatial multiplex systems with multiple antennas. IEEE Transactions on Communications, vol. 54 (10) pp. 1747–1753.CrossRefGoogle Scholar
  32. 32.
    Yu, W. (2006) Sum-capacity computation for the Gaussian vector broadcast channel via dual decomposition. IEEE Transactions on Information Theory, vol. 52 (2) pp. 754–759.CrossRefGoogle Scholar
  33. 33.
    Amraoui, A., Kramer, G. and Shamai (Shitz), S. (2003) Coding for the MIMO broadcast channel. In Proceedings of the IEEE International Symposium on Information Theory, Pacifico Yokohama, Kanagawa, Japan, June 29–July 4, p. 296.CrossRefGoogle Scholar
  34. 34.
    Jafar, S., and Goldsmith, A. (2004) Isotropic fading vector broadcast channels: The scalar upper bound and loss in degrees of freedom. IEEE Transactions on Information Theory, vol. 51 (3) pp. 848–857.CrossRefMathSciNetGoogle Scholar
  35. 35.
    Jindal, N., and Goldsmith, A. (2005) Dirty-paper coding versus TDMA for MIMO broadcast channels. IEEE Transactions on Information Theory, vol. 51 (5) pp. 1783–1794.CrossRefMathSciNetGoogle Scholar
  36. 36.
    Lee, J., and Jindal, N. (2007) High SNR Analysis for MIMO broadcast channels: Dirty paper coding versus linear precoding. IEEE Transactions on Information Theory, vol. 53 (12) pp. 4787–4792.CrossRefMathSciNetGoogle Scholar
  37. 37.
    Sharif, M., and Hassibi, B. (2007) A comparison of time-sharing, DPC, and beamforming for MIMO broadcast channels with many users. IEEE Transactions on Communications, vol. 55 (1) pp. 11–15.CrossRefGoogle Scholar
  38. 38.
    Knopp, R., and Humblet, P. A. (1995) Information capacity and power control in single-cell multi-user communications. In Proceedings of the IEEE International Conference on Communications, Seattle, WA, June, vol. 1, pp. 331–335.Google Scholar
  39. 39.
    Tong, L., Sadler, B. M. and Dong, M. (2004) Pilot-assisted wireless transmissions. IEEE Signal Processing Magazine, vol. 21 (6) pp. 12–25.CrossRefGoogle Scholar
  40. 40.
    Bolcskei, H., Gesbert, D., Papadias, C. B., and Van Der Veen, A.-J. (2006) Space-Time Wireless Systems: From Array Processing to MIMO Communications, Cambridge, UK: Cambridge University Press.Google Scholar
  41. 41.
    Dias, A. R., Bateman, D., and Gosse, K. (2004) Impact of RF front-end impairments and mobility on channel reciprocity for closed-loop multiple antenna techniques. In Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Barcelona, Spain, September 05–08, vol. 2, pp. 1434–1438.Google Scholar
  42. 42.
    Wang, X., and Poor, H. V. (2004) Wireless Communication Systems: Advanced Techniques for Signal Reception. Upper Saddle River, NJ: Prentice-Hall.Google Scholar
  43. 43.
    Verdú, S. (1998) Multiuser Detection. Cambridge, UK: Cambridge University Press.MATHGoogle Scholar
  44. 44.
    Poor, H. V. (2004) Iterative multi-user detection. IEEE Signal Processing Magazine, vol. 21 (1) pp. 81–88.CrossRefGoogle Scholar
  45. 45.
    Foschini, G. J. (1996) Layered space-time architecture for wireless communications in fading environments when using multi-element antennas. Bell Labs Technical Journal, vol. 1 (2) pp. 41–59.CrossRefGoogle Scholar
  46. 46.
    Erez, U., and ten Brink, S. (2005) A close to capacity dirty paper coding scheme. IEEE Transactions on Information Theory, vol. 51 (10) pp. 3417–3432.CrossRefGoogle Scholar
  47. 47.
    Yu, W., Varodayan, D. P., and Cioffi, J. M. (2005) Trellis and convolutional precoding for transmitter-based interference pre-cancellation. IEEE Transactions on Information Theory, vol. 53 (7) pp. 1220–1230.Google Scholar
  48. 48.
    Biglieri, E., Calderbank, R., Constantinides, A., Goldsmith, A., Paulraj, A., and Poor, H. V. (2007) MIMO Wireless Communications, Cambridge, UK: Cambridge University Press.Google Scholar
  49. 49.
    Spencer, Q. H., Swindlehurst, A. L. and Haardt, M. (2004) Zero-forcing methods for the downlink spatial multiplexing in multi-user MIMO channels. IEEE Transactions on Signal Processing, vol.52 (2) pp. 461–471.CrossRefMathSciNetGoogle Scholar
  50. 50.
    Choi, L., and Murch, R. D. (2004) A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach. IEEE Transactions on Wireless Communications, vol. 3 (1) pp. 20–24.CrossRefGoogle Scholar
  51. 51.
    Peel, C. B., Hochwald, B. M., and Swindlehurst, A. L. (2005) A vector perturbation technique for near capacity multiantenna multiuser communication – Part I: Channel inversion and regularization. IEEE Transactions on Communications, vol. 53 (1) pp. 195–202.CrossRefGoogle Scholar
  52. 52.
    Joham, M., Kusume, K., Gzara, M. H., and Utschick, W. (2004) Transmit Wiener filter for the downlink of TDD DS-CDMA systems. In Proceedings of the IEEE Symposium on Spread-Spectrum Technologies and Applications, Lisbon, Portugal, September 15–18, pp. 9–13.Google Scholar
  53. 53.
    Viswanathan, H., Venkatesan, S., and Huang, H. (2003) Downlink capacity evaluation of cellular networks with known-interference cancellation. IEEE Journal on Selected Areas of Communications, vol. 21 (6) pp. 802–811.CrossRefGoogle Scholar
  54. 54.
    Dimić, G., and Sidiropoulos, N. D. (2005) On downlink beamforming with greedy user selection: Performance analysis and a simple new algorithm. IEEE Transactions on Signal Processing, vol. 53 (10) pp. 3857–3868.CrossRefMathSciNetGoogle Scholar
  55. 55.
    Yoo, T., and Goldsmith, A. (2006) On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming. IEEE Journal on Selected Areas in Communications, vol. 25 (7) pp. 1478–1491.CrossRefGoogle Scholar
  56. 56.
    Viswanathan, H., and Kumaran, K. (2001) Rate scheduling in multiple antenna downlink wireless systems. In Proceedings of the Allerton Conference on Communications, Control and Computing, Monticello, IL, USA, September 29 – October 1, vol. 39, pp. 747–756.Google Scholar
  57. 57.
    Chen, R., Heath, R. W., Jr., and Andrews, J. G. (2007) Transmit selection diversity for unitary precoded multiuser spatial multiplexing systems with linear receivers. IEEE Transactions on Information Theory, vol. 55 (3) pp. 1159–1171.MathSciNetGoogle Scholar
  58. 58.
    Shen, Z., Chen, R., Andrews, J. G. and Heath, R. W., Jr. (2006) Low complexity user selection algorithm for multiuser MIMO systems with block diagonalization. IEEE Transactions on Signal Processing, vol. 54 (9) pp. 3658–3663.CrossRefGoogle Scholar
  59. 59.
    Love, D. J., Heath, R. W., Jr., Santipach, W. and Honig, M. L. (2003) What is the value of limited feedback for MIMO channels? IEEE Communications Magazine, vol. 42 (10) pp. 54–59.CrossRefGoogle Scholar
  60. 60.
    Love, D. J., Heath, R. W., Jr., Lau, V. K. N., Gesbert, D., Rao, B. D., and Andrews, M. (2008) An overview of limited feedback in wireless communication systems. IEEE Journal on Selected Areas in Communications. Special issue on Limited Feedback. To appear in October 2008.Google Scholar
  61. 61.
    IEEE Journal on Selected Areas of Communications. Special issue on Limited Feedback. To appear in October 2008.Google Scholar
  62. 62.
    Jindal, N. (2006) MIMO broadcast channels with finite rate feedback. IEEE Transactions on Information Theory, vol. 52 (11) pp. 5045–5059.CrossRefMathSciNetGoogle Scholar
  63. 63.
    Yoo, T., Jindal, N., and Goldsmith, A. (2007) Multi-antenna downlink channels with limited feedback and user selection. IEEE Journal on Selected Areas in Communications, vol. 25 (7) pp. 1478–1491.CrossRefGoogle Scholar
  64. 64.
    Sharif, M., and Hassibi, B. H. (2005) On the capacity of MIMO broadcast with partial side information. IEEE Transactions on Information Theory, vol. 51 (2) pp. 506–522.CrossRefMathSciNetGoogle Scholar
  65. 65.
    Zhang, W., and Letaief, K. B. (2007) MIMO broadcast scheduling with limited feedback. IEEE Journal on Selected Areas in Communications. Special issue on MIMO Transceivers for Realistic Communication Networks: Challenges and Opportunities, vol. 25 (7) pp. 1457–1467.Google Scholar
  66. 66.
    Kountouris, M. and Gesbert, D. (2005) Robust multi-user opportunistic beamforming for sparse networks. In Proceedings of the IEEE Workshop on Signal Processing Advances in Wireless Communications, New York, NY, June 5–8, pp. 975–979.Google Scholar
  67. 67.
    Wagner, J., Liang, Y.-C., and Zhang R. (2007) On the balance of multiuser diversity and spatial multiplexing gain in random beamforming. IEEE Transactions on Wireless Communications. vol. 7 (7) pp. 2512–2525.CrossRefGoogle Scholar
  68. 68.
    Pan, Z., Wong, K.-K., and Ng, T.-S. (2004) Generalized multiuser orthogonal space-division multiplexing. IEEE Transactions on Wireless Communications, vol. 3 (6) pp. 1969–1973.CrossRefGoogle Scholar
  69. 69.
    Chae, C.-B., Mazzarese, D., and Heath, R. W., Jr. (2006) Coordinated beamforming for multiuser MIMO systems with limited feedforward. In Proceedings of the Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, October 30 – November 1, pp. 1511–1515.Google Scholar
  70. 70.
    Chae, C.-B., Mazzarese, D., Jindal, N., and Heath, R. W., Jr. (2008) Coordinated beamforming with limited feedback in the MIMO broadcast channel. IEEE Journal on Selected Areas in Communications. Special issue on Limited Feedback. To appear in October 2008.Google Scholar

Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversita di PisaPisaItaly
  2. 2.Department of Electrical EngineeringPrinceton UniversityPrincetonUSA

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