Abstract
This paper presents a novel method for radio map construction that simultaneously interpolates the received signal power values over space and frequency domains. Radio maps can be used to improve spectrum management and for localization systems, which are related to wireless systems in general such as cellular systems, Internet of Things (IoT) networks, and vehicular communications. Researchers have shown that crowdsourcing using spatial interpolation techniques can be used to accurately construct a radio map to improve these applications; however, because of the limitation in the spatial domain, conventional methods can build a radio map for only those frequencies at which sensing can be performed. Our proposed method focuses on the fact that the shadowing values show strong correlation over a wide range of frequency domains. The main idea is to treat the shadowing values obtained over various frequencies as the ones over target frequency. Using the actual datasets obtained over 870, 2115, and 3500 MHz in a cellular system, we show that the proposed method can accurately generate a radio map, even if no (or few) datasets are available in the target frequency.
Highlights
A RADIO map is a tool for visualizing the spatial distribution of communication quality, such as the average received signal power [2]
The proposed method depends on some radio propagation characteristics such as the shadowing correlation; this fact raises the following fundamental limitations from the viewpoints of arppBleiccaabuisleityt;he proposed method assumes time-invariant shadowing, we may have to periodically update the radio map when it is applied for a time-variant environment (e.g., r indoor environment [6])
We have proposed a powerful method that interpolates the radio map over both space and frequency domains
Summary
A RADIO map is a tool for visualizing the spatial distribution of communication quality, such as the average received signal power [2]. An accurate radio map can enhance the performance of such a radio-mapassisted system (e.g., spectral efficiency in spectrum sharing [2] and localization accuracy in the fingerprint-based localization). This fact has motivated many researchers to study the accurate construction of radio maps. An early work related to this paper was presented at IEEE International Conference on Artificial Intelligence in Information and Communication (ICAIIC) 2020, [1]. The review of this article was coordinated by Dr Guan Gui. (Corresponding author: Koya Sato.)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
