Can I read Two-Stage Radio Map Construction with Real Environments and Sparse Measurements on EtoBox?

Two-Stage Radio Map Construction with Real Environments and Sparse Measurements by Wang, Yifan; Sun, Shu; Liu, Na; Xu, Lianming; Wang, Li is a scholarly article available to read on EtoBox.

What is Two-Stage Radio Map Construction with Real Environments and Sparse Measurements about?

Radio map construction based on extensive measurements is accurate but expensive and time-consuming, while environment-aware radio map estimation reduces the costs at the expense of low accuracy. Considering accuracy and costs, a first-predict-then-correct (FPTC) method is proposed by leveraging generative adversarial networks (GANs). A primary radio map is first predicted by a radio map prediction GAN (RMP-GAN) taking environmental information as input. Then, the prediction result is corrected by a radio map correction GAN (RMC-GAN) with sparse measurements as guidelines. Specifically, the self-attention mechanism and residual-connection blocks are introduced to RMP-GAN and RMC-GAN to improve the accuracy, respectively. Experimental results validate that the proposed FPTC-GANs method achieves the best radio map construction performance, compared with the state-of-the-art methods.

Author

Wang, Yifan; Sun, Shu; Liu, Na; Xu, Lianming; Wang, Li

Published

2024

Language

EN