Skip to main content

Transmission Strategies in MIMO Ad Hoc Networks


Precoding problem in multiple-input multiple-output (MIMO) ad hoc networks is addressed in this work. Firstly, we consider the problem of maximizing the system mutual information under a power constraint. In this context, we give a brief overview of the nonlinear optimization methods, and systematically we compare their performances. Then, we propose a fast and distributed algorithm based on the quasi-Newton methods to give a lower bound of the system capacity of MIMO ad hoc networks. Our proposed algorithm solves the maximization problem while diminishing the amount of information in the feedback links needed in the cooperative optimization. Secondly, we propose a different problem formulation, which consists in minimizing the total transmit power under a quality of signal constraint. This novel problem design is motivated since the packets are captured in ad hoc networks based on their signal-to-interference-plus-noise ratio (SINR) values. We convert the proposed formulation into semidefinite optimization problem, which can be solved numerically using interior point methods. Finally, an extensive set of simulations validates the proposed algorithms.

Publisher note

To access the full article, please see PDF.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Khalil Fakih.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Fakih, K., Diouris, JF. & Andrieux, G. Transmission Strategies in MIMO Ad Hoc Networks. J Wireless Com Network 2009, 128098 (2009).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI:


  • Mutual Information
  • Interior Point
  • Nonlinear Optimization
  • Point Method
  • Maximization Problem