This article is part of the series Distributed Space-Time Systems.

Open Access Research Article

Cooperative Multibeamforming in Ad Hoc Networks

Chuxiang Li1 and Xiaodong Wang2*

Author Affiliations

1 Marvell Semiconductor, Inc., Santa Clara, CA 95054, USA

2 Department of Electrical Engineering, Columbia University, New York, NY 10027, USA

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EURASIP Journal on Advances in Signal Processing 2008, 2008:310247  doi:10.1155/2008/310247

The electronic version of this article is the complete one and can be found online at:

Received: 24 April 2007
Revisions received: 6 August 2007
Accepted: 8 October 2007
Published: 22 October 2007

© 2008 The Author(s).

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We treat the problem of cooperative multiple beamforming in wireless ad hoc networks. The basic scenario is that a cluster of source nodes cooperatively forms multiple data-carrying beams toward multiple destination nodes. To resolve the hidden node problem, we impose a link constraint on the receive power at each unintended destination node. Then the problem becomes to optimize the transmit powers and beam weights at the source cluster subject to the maximal transmit power constraint, the minimal receive signal-to-interference-plus-noise ratio (SINR) constraints at the destination nodes, and the minimal receive power constraints at the unintended destination nodes. We first propose an iterative transmit power allocation algorithm under fixed beamformers subject to the maximal transmit power constraint, as well as the minimal receive SINR and receive power constraints. We then develop a joint optimization algorithm to iteratively optimize the powers and the beamformers based on the duality analysis. Since channel state information (CSI) is required by the sources to perform the above optimization, we further propose a cooperative scheme to implement a simple CSI estimation and feedback mechanism based on the subspace tracking principle. Simulation results are provided to demonstrate the performance of the proposed algorithms.

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