4 research outputs found
Are Slepian-Wolf Rates Necessary for Distributed Parameter Estimation?
We consider a distributed parameter estimation problem, in which multiple
terminals send messages related to their local observations using limited rates
to a fusion center who will obtain an estimate of a parameter related to
observations of all terminals. It is well known that if the transmission rates
are in the Slepian-Wolf region, the fusion center can fully recover all
observations and hence can construct an estimator having the same performance
as that of the centralized case. One natural question is whether Slepian-Wolf
rates are necessary to achieve the same estimation performance as that of the
centralized case. In this paper, we show that the answer to this question is
negative. We establish our result by explicitly constructing an asymptotically
minimum variance unbiased estimator (MVUE) that has the same performance as
that of the optimal estimator in the centralized case while requiring
information rates less than the conditions required in the Slepian-Wolf rate
region.Comment: Accepted in Allerton 201