CKMImageNet: A Comprehensive Dataset to Enable Channel Knowledge Map Construction via Computer Vision
Di Wu, Zijian Wu, Yuelong Qiu, Shen Fu, Yong Zeng

TL;DR
This paper introduces CKMImageNet, a large-scale dataset combining location-tagged channel data and visual images to facilitate environment-aware communication and the construction of channel knowledge maps using computer vision techniques.
Contribution
The paper presents CKMImageNet, the first dataset to integrate visual environment data with channel information for AI-driven CKM construction.
Findings
Supports verification of communication algorithms
Enables CKM construction with computer vision
Reveals relationships between environment and channel knowledge
Abstract
Environment-aware communication and sensing is one of the promising paradigm shifts towards 6G, which fully leverages prior information of the local wireless environment to optimize network performance. One of the key enablers for environment-aware communication and sensing is channel knowledge map (CKM), which provides location-specific channel knowledge that is crucial for channel state information (CSI) acquisition. To support the efficient construction of CKM, large-scale location-specific channel data is essential. However, most existing channel datasets do not have the location information nor visual representations of channel data, making them inadequate for exploring the intrinsic relationship between the channel knowledge and the local environment, nor for applying advanced artificial intelligence (AI) algorithms such as computer vision (CV) for CKM construction. To address…
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Taxonomy
TopicsAdvanced Computational Techniques and Applications
