Converses for distributed estimation via strong data processing inequalities
Converses for distributed estimation via strong data processing inequalities
We consider the problem of distributed estimation, where local processors observe independent samples conditioned on a common random parameter of interest, map the observations to a finite number of bits, and send these bits to a remote estimator over independent noisy channels. We derive converse results for this problem, such …