Distributed Hypothesis Testing with Collaborative Detection
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A detection system with a single sensor and two detectors is considered, where each of the terminals observes a memoryless source sequence, the sensor sends a message to both detectors and the first detector sends a message to the second detector. Communication of these messages is assumed to be error-free but rate-limited. The joint probability mass function (pmf) of the source sequences observed at the three terminals depends on an M-ary hypothesis (M≥ 2), and the goal of the communication is that each detector can guess the underlying hypothesis. Detector k, k=1,2, aims to maximize the error exponent under hypothesis i_k, i_k ∈{1,...,M}, while ensuring a small probability of error under all other hypotheses. We study this problem in the case in which the detectors aim to maximize their error exponents under the same hypothesis (i.e., i_1=i_2) and in the case in which they aim to maximize their error exponents under distinct hypotheses (i.e., i_1 ≠ i_2). For the setting in which i_1=i_2, we present an achievable exponents region for the case of positive communication rates, and show that it is optimal for a specific case of testing against independence. We also characterize the optimal exponents region in the case of zero communication rates. For the setting in which i_1 ≠ i_2, we characterize the optimal exponents region in the case of zero communication rates.
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