Grassmannian predictive coding for delayed limited feedback MIMO systems

  • Authors:

  • Takao Inoue;Robert W. Heath, Jr.

  • Affiliations:

  • The University of Texas at Austin, Department of Electrical and Computer Engineering, Wireless Networking and Communication Group, Austin, TX;The University of Texas at Austin, Department of Electrical and Computer Engineering, Wireless Networking and Communication Group, Austin, TX

  • Venue:
  • Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
  • Year:
  • 2009

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Abstract

Limited feedback in multiple antenna wireless systems is a practical technique to obtain channel state information at the transmitter. When the channel is time-varying with memory, however, selected codeword may become outdated before its use at the transmitter. To overcome this problem, we propose a Grassmannian prediction and predictive coding framework for delayed feedback systems by exploiting the memory in the channel. A prediction step size optimization criterion for correlated time-series evolving on the Grassmann manifold is derived. The proposed predictive coding framework uses optimized prediction to account for the feedback delay. Application to delayed limited feedback multiuser multiple antenna system shows sum rate improvement and robustness to delay.