On optimal channel training for uplink network MIMO systems

Jakob Hoydis, Mari Kobayashi, Mérouane Debbah

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

We study a multi-cell frequency-selective fading uplink channel from K user terminals (UTs) to B base stations (BSs). The BSs, assumed to be oblivious of the applied encoding scheme, compress and forward their observations to a central station (CS) via capacity limited backhaul links. The CS jointly decodes the messages from all UTs. Since we assume no prior channel state information, the channel needs to be estimated during its coherence time. Based on a lower bound of the ergodic mutual information, we determine the optimal fraction of the coherence time used for channel training. We then study how the optimal training length is impacted by the backhaul capacity. Our analysis is based on large random matrix theory but shown by simulations to be tight for even small system dimensions.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3056-3059
Number of pages4
ISBN (Print)9781457705397
DOIs
StatePublished - 2011
Externally publishedYes

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Keywords

  • Coordinated Multi-Point (CoMP)
  • channel estimation
  • network MIMO
  • random matrix theory

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