Decentralized Sequential Hypothesis Testing Using Asynchronous Communication

Abstract

An asymptotically optimum test for the problem of decentralized sequential hypothesis testing is presented. The induced communication between sensors and fusion center is asynchronous and limited to 1-bit data. When the sensors observe continuously stochastic processes with continuous paths, the proposed test is order-2 asymptotically optimal, in the sense that its inflicted performance loss is bounded. When the sensors take discrete time observations, the proposed test achieves order-1 asymptotic optimality, i.e., the ratio of its performance over the optimal performance tends to 1. Moreover, we show theoretically and corroborate with simulations that the performance of the suggested test in discrete time can be significantly improved when the sensors sample their underlying continuous time processes more frequently, a property which is not enjoyed by other centralized or decentralized tests in the literature.