THE DATA/IDENTITY TRADEOFF WITH CENSORED SENSORS

All practical sensing operations must work with quantized data. Along with measurements, each sensor is assumed to have some label value that is relevant to its stochastic measurement parameterization and must be communicated to the decision center. We are interested in cases that require very low communication cost, and thus require very coarse quantization of the measurements as well as the labels (2-bit values, for instance). Censoring is used to control the expected communication cost-each sensor decides locally whether or not to send its data to the decision center based on the value of its label as well as the value of its measurement. In this work we formalize the test statistic based on censored and quantized data.

Automated summary

This work formalizes the test statistic based on censored and quantized data, focusing on cases that require very low communication cost. The measurements and labels are quantized in a coarse manner (e.g., 2-bit values), and censoring is used to control the expected communication cost.