@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} }