IMNet: Interference-Aware Channel Knowledge Map Construction and Localization

Le Zhao; Zesong Fei; Xinyi Wang; Jingxuan Huang; Yuan Li; Yan Zhang

doi:10.1109/LWC.2025.3526222

IMNet: Interference-Aware Channel Knowledge Map Construction and Localization

Le Zhao, Zesong Fei, Xinyi Wang^*, Jingxuan Huang, Yuan Li, Yan Zhang

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

This letter presents a novel two-stage method for constructing channel knowledge maps (CKMs) specifically for A2G (Aerial-to-Ground) channels in the presence of non-cooperative interfering nodes (INs). We first estimate the interfering signal strength (ISS) at sampling locations based on total received signal strength measurements and the desired communication signal strength (DSS) map constructed with environmental topology. Next, an ISS map construction network (IMNet) is proposed, where a negative value correction module is included to enable precise reconstruction. Subsequently, we further execute signal-to-interference-plus-noise ratio map construction and IN localization. Simulation results demonstrate lower construction error of the proposed IMNet compared to baselines in the presence of interference.

Original language	English
Pages (from-to)	856-860
Number of pages	5
Journal	IEEE Wireless Communications Letters
Volume	14
Issue number	3
DOIs	https://doi.org/10.1109/LWC.2025.3526222
Publication status	Published - 2025

Keywords

Channel knowledge map
deep learning
interference localization
interfering signal strength

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10.1109/LWC.2025.3526222

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title = "IMNet: Interference-Aware Channel Knowledge Map Construction and Localization",

abstract = "This letter presents a novel two-stage method for constructing channel knowledge maps (CKMs) specifically for A2G (Aerial-to-Ground) channels in the presence of non-cooperative interfering nodes (INs). We first estimate the interfering signal strength (ISS) at sampling locations based on total received signal strength measurements and the desired communication signal strength (DSS) map constructed with environmental topology. Next, an ISS map construction network (IMNet) is proposed, where a negative value correction module is included to enable precise reconstruction. Subsequently, we further execute signal-to-interference-plus-noise ratio map construction and IN localization. Simulation results demonstrate lower construction error of the proposed IMNet compared to baselines in the presence of interference.",

keywords = "Channel knowledge map, deep learning, interference localization, interfering signal strength",

author = "Le Zhao and Zesong Fei and Xinyi Wang and Jingxuan Huang and Yuan Li and Yan Zhang",

note = "Publisher Copyright: {\textcopyright} 2012 IEEE.",

year = "2025",

doi = "10.1109/LWC.2025.3526222",

language = "English",

volume = "14",

pages = "856--860",

journal = "IEEE Wireless Communications Letters",

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TY - JOUR

T1 - IMNet

T2 - Interference-Aware Channel Knowledge Map Construction and Localization

AU - Zhao, Le

AU - Fei, Zesong

AU - Wang, Xinyi

AU - Huang, Jingxuan

AU - Li, Yuan

AU - Zhang, Yan

PY - 2025

Y1 - 2025

N2 - This letter presents a novel two-stage method for constructing channel knowledge maps (CKMs) specifically for A2G (Aerial-to-Ground) channels in the presence of non-cooperative interfering nodes (INs). We first estimate the interfering signal strength (ISS) at sampling locations based on total received signal strength measurements and the desired communication signal strength (DSS) map constructed with environmental topology. Next, an ISS map construction network (IMNet) is proposed, where a negative value correction module is included to enable precise reconstruction. Subsequently, we further execute signal-to-interference-plus-noise ratio map construction and IN localization. Simulation results demonstrate lower construction error of the proposed IMNet compared to baselines in the presence of interference.

AB - This letter presents a novel two-stage method for constructing channel knowledge maps (CKMs) specifically for A2G (Aerial-to-Ground) channels in the presence of non-cooperative interfering nodes (INs). We first estimate the interfering signal strength (ISS) at sampling locations based on total received signal strength measurements and the desired communication signal strength (DSS) map constructed with environmental topology. Next, an ISS map construction network (IMNet) is proposed, where a negative value correction module is included to enable precise reconstruction. Subsequently, we further execute signal-to-interference-plus-noise ratio map construction and IN localization. Simulation results demonstrate lower construction error of the proposed IMNet compared to baselines in the presence of interference.

KW - Channel knowledge map

KW - deep learning

KW - interference localization

KW - interfering signal strength

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DO - 10.1109/LWC.2025.3526222

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SP - 856

EP - 860

JO - IEEE Wireless Communications Letters

JF - IEEE Wireless Communications Letters

IS - 3

ER -

IMNet: Interference-Aware Channel Knowledge Map Construction and Localization

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