Abstract
We address the optimal quantizer design problem for distributed Bayesian parameter estimation where each sensor quantizes its local observation into one bit and transmit it through non-ideal channels to the Fusion Center. We first develop an asymptotic performance limit (PL) as a performance bound for any quantizer design with a known prior. Aided by this PL, we derive the optimal quantizer and near optimal quantizer with set of observation models that achieves the PL, thus solve a set of optimal quantizer design problem for distributed estimation.
Original language | American English |
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Journal | Electrical and Computer Engineering Faculty Publications and Presentations |
State | Published - 1 Jan 2021 |
Keywords
- Cramer-Rao lower bound
- One-bit quantization
- asymptotic performance limit
- distributed Bayesian estimation
- non-ideal channel
EGS Disciplines
- Electrical and Computer Engineering