Open Access

Mode Switching for the Multi-Antenna Broadcast Channel Based on Delay and Channel Quantization

  • Jun Zhang1Email author,
  • Robert W. HeathJr.1,
  • Marios Kountouris1 and
  • Jeffrey G. Andrews1
EURASIP Journal on Advances in Signal Processing20092009:802548

https://doi.org/10.1155/2009/802548

Received: 16 December 2008

Accepted: 23 April 2009

Published: 7 June 2009

Abstract

Imperfect channel state information degrades the performance of multiple-input multiple-output (MIMO) communications; its effects on single-user (SU) and multiuser (MU) MIMO transmissions are quite different. In particular, MU-MIMO suffers from residual interuser interference due to imperfect channel state information while SU-MIMO only suffers from a power loss. This paper compares the throughput loss of both SU and MU-MIMO in the broadcast channel due to delay and channel quantization. Accurate closed-form approximations are derived for achievable rates for both SU and MU-MIMO. It is shown that SU-MIMO is relatively robust to delayed and quantized channel information, while MU-MIMO with zero-forcing precoding loses its spatial multiplexing gain with a fixed delay or fixed codebook size. Based on derived achievable rates, a mode switching algorithm is proposed, which switches between SU and MU-MIMO modes to improve the spectral efficiency based on average signal-to-noise ratio (SNR), normalized Doppler frequency, and the channel quantization codebook size. The operating regions for SU and MU modes with different delays and codebook sizes are determined, and they can be used to select the preferred mode. It is shown that the MU mode is active only when the normalized Doppler frequency is very small, and the codebook size is large.

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Authors’ Affiliations

(1)
Wireless Networking and Communications Group, Department of Electrical and Computer Engineering, The University of Texas at Austin

Copyright

© Jun Zhang et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.