.png){kind=icon}
返回
A Low-Complexity Soft Localization Algorithm Based on Expectation Propagation
.png){kind=icon}
PRE
AI
DOI：10.1109/LCOMM.2023.3323768.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Location awareness enables applications that rely on positional information contained in wireless signals. However, fully extracting this information and utilizing it with low complexity remains challenging. In this letter, we introduce a low-complexity soft localization algorithm based on expectation propagation (EP). Firstly, we construct a factor graph for soft localization, which involves complex local functions. Next, a latent variable is introduced to simplify these functions, resulting in a new factor graph. Leveraging this graph, we develop an efficient soft localization algorithm based on EP. Finally, simulation results demonstrate that the proposed algorithm can achieve precise localization with low computational complexity.
Keyword:
Soft localization
factor graphs
expectation propagation
low complexity
期刊
IF:
4.4
论文数:
1.3W
被引数:
2.2W
机构
引用论文
An Auxiliary Variable-Aided Hybrid Message Passing Approach to Joint Channel Estimation and Decoding for MIMO-OFDMMimo-ofdm联合信道估计和解码的辅助变量辅助混合消息传递方法
PREAI
分享收藏
A Flavo-Diiron Protein from Desulfovibrio vulgaris with Oxidase and Nitric Oxide Reductase Activities. Evidence for an in Vivo Nitric Oxide Scavenging Function.png)
Biochemistry
BiochemistryIF0
PREAI
分享收藏
Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Toward 6G蜂窝、广域和非地面物联网: 关于5g进展和6g道路的调查
PREAI
分享收藏
查看更多内容