Acquisition of Channel State Information For Adaptive Transmission

Doctoral Dissertation

Abstract

Adaptive transmission systems improve the throughput of wireless communication systems by utilizing some knowledge of the channel state to adapt or allocate transmitter resources. This dissertation investigates the acquisition of channel state information for adaptive transmission systems. Departing from the common assumption that the feedback channel is error free, we model the feedback channel as a practical wireless channel with fading and additive noise attributes. We show that feedback errors could significantly reduce the gains promised by adaptive transmission. Subsequently, we propose feedback receivers that exploit some knowledge of the channel statistics to mitigate the performance degradation caused by the feedback channel. This work is extended to multiuser systems, where new problems are investigated, namely, quantization errors coupled with feedback errors, and multi-access interference. system. Finally, we consider CSI acquisition for transmit antenna selection and discuss the tradeoffs between capacity gain and training. A reduced complexity suboptimal search algorithm is also developed using the channel’s temporal correlation.

Attributes

Attribute NameValues
URN
  • etd-04212006-112847

Author Anthony Edet Ekpenyong
Advisor Tom Fuja
Contributor Tom Fuja, Committee Member
Contributor Yih-Fang Huang, Committee Member
Contributor Daniel Costello, Committee Member
Degree Level Doctoral Dissertation
Degree Discipline Electrical Engineering
Degree Name PhD
Defense Date
  • 2006-04-11

Submission Date 2006-04-21
Country
  • United States of America

Subject
  • Bayesian detection

  • Markov channels

  • adaptive modulation

  • channel state information

Publisher
  • University of Notre Dame

Language
  • English

Record Visibility and Access Public
Content License
  • All rights reserved

Departments and Units

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