A Fundamental Limit of Distributed Hypothesis Testing Under Memoryless Quantization
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Abstract (arXiv)
We study a distributed hypothesis testing setup where peripheral nodes send quantized data to the fusion center in a memoryless fashion. The expected number of bits sent by each node under the null hypothesis is kept limited. We characterize the optimal decay rate of the mis-detection (type-II error) probability provided that false alarms (type-I error) are rare, and study the tradeoff between the communication rate and maximal type-II error decay rate. We resort to rate-distortion methods to provide upper bounds to the tradeoff curve and show that at high rates lattice quantization achieves near-optimal performance. We also characterize the tradeoff for the case where nodes are allowed to record and quantize a fixed number of samples. Moreover, under sum-rate constraints, we show that an upper bound to the tradeoff curve is obtained with a water-filling solution.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jun 2022.
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.
- 2023On the Fusion Strategies for Federated Decision Makingcited by 1
- 2024Causal Influence in Federated Edge Inferencecited by 1
- 2024Causal Influence in Federated Edge Inference2 May 2024
- 2023On the Fusion Strategies for Federated Decision Making10 Mar 2023