Computer Science – Information Theory
Scientific paper
2008-10-09
The 46th Annual Allerton Conference on Communication, Control and Computing, Allerton House, Illinois, Sept. 2008
Computer Science
Information Theory
8 pages, 3 figures, appeared in the 46th Annual Allerton Conference on Communication, Control and Computing, Allerton House, I
Scientific paper
10.1109/ALLERTON.2008.4797617
Recent result shows how to compute distributively and efficiently the linear MMSE for the multiuser detection problem, using the Gaussian BP algorithm. In the current work, we extend this construction, and show that operating this algorithm twice on the matching inputs, has several interesting interpretations. First, we show equivalence to computing one iteration of the Kalman filter. Second, we show that the Kalman filter is a special case of the Gaussian information bottleneck algorithm, when the weight parameter $\beta = 1$. Third, we discuss the relation to the Affine-scaling interior-point method and show it is a special case of Kalman filter. Besides of the theoretical interest of this linking estimation, compression/clustering and optimization, we allow a single distributed implementation of those algorithms, which is a highly practical and important task in sensor and mobile ad-hoc networks. Application to numerous problem domains includes collaborative signal processing and distributed allocation of resources in a communication network.
Bickson Danny
Dolev Danny
Shental Ori
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