@article{
  author = {H. Paul and J. Fliege and A. Dekorsy},
  year = {2013},
  month = {Jan},
  title = {In-Network-Processing: Distributed Consensus-Based Linear Estimation},
  volume = {17},
  number = {1},
  publisher = {IEEE Communications Letters},
  pages = {59-62 },
  abstract={In a cooperative broadcast scenario, a group of nodes in a network aims to reconstruct a common message. In this paper, we present a new algorithm for distributed consensus-based estimation in such scenarios. Possible applications comprise mobile communication systems and sensor networks. Starting with a least squares estimation problem, the algorithm is developed using techniques from optimization theory. The required communication effort for parallel implementation in a resource-constrained network is estimated and compared to existing approaches. We show that the proposed algorithm requires fewer iterations and a reduced communication overhead per iteration while keeping the estimation accuracy. A modification of the algorithm based on an approximation is presented, which reduces the communication effort even further. All results are corroborated by computer simulations considering different system parameters.
},
  journal={IEEE Communications Letters}
}