.png){kind=icon}
返回
Spectrum Sensing Based on Graph Weighted Aggregation Operator
.png){kind=icon}
PRE
AI
DOI：10.1109/LCOMM.2023.3314805.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Signal processing on graph provides a promising perspective for spectrum sensing. The existing graph-based methods only employ the converted unweighted graph feature but ignore the edge weight and the graph signal information based on the signal-to-graph conversion mechanism. In this letter, we propose a graph-based detector by fully exploiting and merging weighted graph feature and graph signal. In particular, we first propose an improved graph representation framework to convert the power spectrum of the received signal into weighted graph and map that into graph signal. Subsequently, the weighed graph feature of the converted graph is characterized. On this basis, we propose a graph weighted aggregation operator to jointly combine the graph signal and weighted graph feature. Monte Carlo simulation results demonstrate that the proposed method is significantly superior to the existing graph-based methods and energy detection particularly for low signal-to-noise regions.
Keyword:
Spectrum sensing
weighted graph representa-tion
graph signals
graph weighted aggregation operator
期刊
IF:
4.4
论文数:
1.3W
被引数:
2.2W
机构
暂无机构信息
引用论文
Contribution of mononuclear leucocytes to the progression of experimental focal glomerular sclerosis
OAAI
OAAI分享收藏Graph-based confidence verification for BPSK signal analysis under low SNRs.png)
SIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏A visibility graph power averaging aggregation operator: A methodology based on network analysis
PREAI
分享收藏 没有更多内容
没有更多内容