Analysing bit-interleaved coded modulation in multiple-input multiple-output systems with channel estimation error

Analysing bit-interleaved coded modulation in multiple-input multiple-output systems with channel estimation error

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The performance of bit-interleaved coded modulation in multiple-input multiple-output (BICM-MIMO) systems using an iterative channel estimator is analysed. In a conventional iterative channel estimator, after initialisation with the training phase, the channel estimator switches to the data phase. However, such a conventional iterative channel estimator does not always improve the performance of the receiver. In order to guarantee the performance improvement, a condition on when the output of the decoder should be used by the estimator is determined. Such a condition is related to the reliability of the soft information utilised by the channel estimator. The key in establishing this relationship is to use the mutual information (MI) that the observation vector has about the channel gains given the output of the decoder at each iteration. In this switch-augmented conventional iterative channel estimator, referred to as SAICE, the condition is theoretically found and indicates the needed reliability of the soft information for the channel estimator at the switching time. The switch-augmented scheme guarantees performance improvement of the iterative receiver with each iteration, however, it might need many iterations to converge for moderate to low signal-to-noise ratios (SNRs). A less computationally intensive approach is to use both the training and data segments of the observation. This approach produces a combined iterative channel estimator (CICE) for BICM-MIMO systems. The performance behaviour of the BICM-MIMO system is illustrated through the extrinsic information transfer (EXIT) chart with imperfect channel state information (CSI). Analytical results are verified with computer simulations.


    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
      • Lai, I.-W., Godtmann, S., Chiueh, T.-D., Ascheid, G., Meyr, H.: `Asymptotic BER analysis for MIMO-BICM with zero-forcing detectors assuming imperfect CSI', Proc. IEEE Int. Conf. Commun., May 2008, p. 1238–1242.
    12. 12)
    13. 13)
      • Y. nan Lee , A. Ashikhmin , J.-T. Chen . Impact of soft channel construction on iterative channel estimation and data decoding for multicarrier systems. IEEE Trans. Commun. , 2762 - 2770
    14. 14)
    15. 15)
      • Novak, C., Lechner, G., Matz, G.: `MIMO-BICM with imperfect channel state information: EXIT chart analysis and LDPC code optimization', Proc. Asilomar Conf. Signals, System Computers, 2008, p. 443–447.
    16. 16)
    17. 17)
      • N. Gresset , J.J. Boutros , L. Brunel . (2004) Optimal linear precoding for BICM over MIMO channels.
    18. 18)
      • T.M. Cover , J.A. Thomas . (2006) Elements of information theory.
    19. 19)
    20. 20)

Related content

This is a required field
Please enter a valid email address