Chapter 8. Convex Optimization Theory Applied to Joint Transmitter-Receiver Design in MIMO Channels

  1. A. B. Gershman5,6 and
  2. N. D. Sidiropoulos7
  1. Daniel Pérez Palomar1,
  2. Antonio Pascual-Iserte2,
  3. John M. Cioffi3 and
  4. Miguel Angel Lagunas2,4

Published Online: 30 JUN 2005

DOI: 10.1002/0470010045.ch8

Space-Time Processing for MIMO Communications

Space-Time Processing for MIMO Communications

How to Cite

Palomar, D. P., Pascual-Iserte, A., Cioffi, J. M. and Lagunas, M. A. (2005) Convex Optimization Theory Applied to Joint Transmitter-Receiver Design in MIMO Channels, in Space-Time Processing for MIMO Communications (eds A. B. Gershman and N. D. Sidiropoulos), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/0470010045.ch8

Editor Information

  1. 5

    McMaster University, Hamilton, ON, Canada

  2. 6

    University of Duisburg-Essen, Duisburg, Germany

  3. 7

    Technical University of Crete, Crete, Greece

Author Information

  1. 1

    Princeton University, Princeton, NJ, USA

  2. 2

    Technical University of Catalonia, Barcelona, Spain

  3. 3

    Stanford University, Stanford, CA, USA

  4. 4

    Telecommunications Technological Center of Catalonia, Barcelona, Spain

Publication History

  1. Published Online: 30 JUN 2005
  2. Published Print: 22 APR 2005

ISBN Information

Print ISBN: 9780470010020

Online ISBN: 9780470010044

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Keywords:

  • convex optimization theory;
  • quadratically constrained quadratic program;
  • Lagrange duality theory;
  • primal problem;
  • dual variables;
  • duality gap;
  • barrier methods;
  • finite impulse response (FIR);
  • beamforming

Summary

This chapter contains sections titled:

  • Introduction

  • Convex Optimization Theory

  • System Model and Preliminaries

  • Beamforming Design for MIMO Channels: A Convex Optimization Approach

  • An Application to Robust Transmitter Design in MIMO Channels

  • Summary

  • References