Distributed beamforming for information transfer in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Collaborative beamforming for distributed wireless ad hoc sensor networks
IEEE Transactions on Signal Processing
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Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks
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On the power efficiency of sensory and ad hoc wireless networks
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Blind beamforming on a randomly distributed sensor array system
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IEEE Journal on Selected Areas in Communications
Cooperative beamforming for multi-hop relaying in wireless sensor networks
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Weighted cross-layer cooperative beamforming for wireless networks
IEEE Transactions on Signal Processing
Network beamforming using relays with perfect channel information
IEEE Transactions on Information Theory
Iterative limited feedback beamforming for MIMO ad-hoc networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Interference cancellation in distributed space-time coded wireless relay networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
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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.