Nonparametric one-bit quantizers for distributed estimation

In this paper, we consider the distributed parameter estimation problem using one-bit quantized data from local sensors. Nonparametric distributed estimators are proposed based on knowledge of the moments of sensor noise. These estimators are shown to be either unbiased or asymptotically unbiased with bounded estimation variance for all possible parameter values. Relationship between the proposed approaches and dithering in quantization is investigated. Performance comparison is made between the proposed estimators and the Sign quantizer via an illustrative example.