作者
Chengxi Li, You He, Xueqian Wang, Gang Li, Pramod K Varshney
发表日期
2019/10/2
期刊
IEEE Signal Processing Letters
卷号
26
期号
12
页码范围
1738-1742
出版商
IEEE
简介
In this letter, we consider the detection of sparse stochastic signals with sensor networks (SNs), where the fusion center (FC) collects 1-bit data from the local sensors and then performs global detection. For this problem, a newly developed 1-bit locally most powerful test (LMPT) detector requires 3.3Q sensors to asymptotically achieve the same detection performance as the centralized LMPT (cLMPT) detector with Q sensors. This 1-bit LMPT detector is based on 1-bit quantized observations without any additional processing at the local sensors. However, direct quantization of observations is not the most efficient processing strategy at the sensors since it incurs unnecessary information loss. In this letter, we propose an improved-1-bit LMPT (Im-1-bit LMPT) detector that fuses local 1-bit quantized likelihood ratios (LRs) instead of directly quantized local observations. In addition, we design the quantization thresholds …
学术搜索中的文章
C Li, Y He, X Wang, G Li, PK Varshney - IEEE Signal Processing Letters, 2019