存在不可靠上报信道的量化但未编码分布式检测（QDD）
Quantized-but-uncoded Distributed Detection (QDD) with Unreliable Reporting Channels
AI总结：
该研究提出量化但未编码分布式检测（QDD）方法，验证其适配传输功率约束的特性，推导独立观测下的最优决策规则，并通过数值实验对比不同检测系统的性能。
摘要：
分布式检测主要围绕两类方法展开：未量化分布式检测（Unquantized Distributed Detection, UDD），即每个传感器将其完整观测值上报给融合中心（fusion center, FC）；以及量化编码分布式检测（quantized-and-Coded DD, CDD），即每个传感器先对观测空间进行划分，再向融合中心上报一个码字。本文提出了量化但未编码分布式检测（Quantized-but-uncoded DD, QDD）：每个传感器完成量化后，向融合中心传输一个汇总值而非码字。研究表明，与CDD相比，QDD能更好地适配传输功率约束，不过参数选择的复杂度有所提升。此外，本文证明在观测独立的情况下，QDD满足CDD固有的一个必要条件：具体而言，最优传感器决策规则为似然比量化器（likelihood ratio quantizers, LRQ），与信道条件无关。在传感器端执行二元决策的单传感器场景下，研究发现QDD中的最优传感器规则通常不再具备CDD所具有的“信道盲”特性。另外，本文在传感和上报阶段均存在加性高斯白噪声（additive white Gaussian noise, AWGN）的假设下，在相同传输功率和带宽条件下对这些系统进行了数值比较。最后，本文提出了一些未来研究的潜在方向。
英文摘要：
Distributed detection primarily centers around two approaches: Unquantized Distributed Detection (UDD), where each sensor reports its complete observation to the fusion center (FC), and quantized-and-Coded DD (CDD), where each sensor first partitions the observation space and then reports to the FC a codeword. In this paper, we introduce Quantized-but-uncoded DD (QDD), where each sensor, after quantization, transmits a summarized value, instead of a codeword, to the FC. We show that QDD well adapts to the constraint of transmission power when compared to CDD, albeit with increased complexity in parameter selection. Moreover, we establish that, in the presence of independent observations, QDD upholds a necessary condition inherent in CDD. Specifically, the optimal sensor decision rules are the likelihood ratio quantizers (LRQ), irrelevant to the channel conditions. In the context of a single-sensor scenario involving binary decision at the sensor, we find that the optimal sensor rule in QDD is in general no longer ``channel blind", a feature presented in CDD. In addition, we compare these systems numerically under the same transmission power and bandwidth, while assuming additive white Gaussian noise (AWGN) in both sensing and reporting stages. Finally, we present some potential directions for future research.
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