EMI Characteristics Informed JSPA-BR Approach for Sensing, Networking, and Computing Integrated Aerial IoT Applications

The next generation of industrial internet of things (IoT) dominated by unmanned aerial vehicle (UAV) relies on the coordinated operation of heterogeneous UAV-mounted transceiver cluster (HUTC) in constrained environments. However, the electromagnetic resources available to these transceivers deployed in crowded spaces are limited, and the resulting spectrum conflicts can easily lead to difficulties in aerial sensing, computing, and networking. Beyond interference from external sources, spectrum allocation in dense spaces is further complicated by interference from frequency-domain neighbors, making efficient resource allocation challenging. Thus, this article utilize the electromagnetic interference (EMI) characteristics of heterogeneous transceivers as prior knowledge and proposes an innovative joint spectrum and power allocation based on better response (JSPA-BR) method to tackle the EMI problem in HUTC composed of heterogeneous transceivers. More specifically, we construct a game-theoretic model for joint spectrum and power allocation, and it is proved that the model constitutes an exact potential game (EPG) with at least one Nash equilibrium (NE) point. We then design the JSPA-BR algorithm which can converge quickly and approach the global optimal solution. Simulations and measurements show that this method maximizes the use of limited spectrum resources. It also mitigates EMI between transceivers and the external radiation of the system. It achieves electromagnetic compatibility of HUTC, thereby demonstrating the effectiveness and accuracy of the proposed approach.

Authors

Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-05-26
DOI
https://doi.org/10.1109/jiot.2025.3573325
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EMI Characteristics Informed JSPA-BR Approach for Sensing, Networking, and Computing Integrated Aerial IoT Applications

Chinmay Chakraborty, Youwei Meng, Xin Jian, Yaoyao Li et al.
IEEE Internet of Things Journal
Air Traffic Management and Optimization
article

EMI Characteristics Informed JSPA-BR Approach for Sensing, Networking, and Computing Integrated Aerial IoT Applications

Chinmay Chakraborty, Youwei Meng, Xin Jian, Yaoyao Li, Houpu Xiao, Fahad Alblehai
article en

Abstract

The next generation of industrial internet of things (IoT) dominated by unmanned aerial vehicle (UAV) relies on the coordinated operation of heterogeneous UAV-mounted transceiver cluster (HUTC) in constrained environments. However, the electromagnetic resources available to these transceivers deployed in crowded spaces are limited, and the resulting spectrum conflicts can easily lead to difficulties in aerial sensing, computing, and networking. Beyond interference from external sources, spectrum allocation in dense spaces is further complicated by interference from frequency-domain neighbors, making efficient resource allocation challenging. Thus, this article utilize the electromagnetic interference (EMI) characteristics of heterogeneous transceivers as prior knowledge and proposes an innovative joint spectrum and power allocation based on better response (JSPA-BR) method to tackle the EMI problem in HUTC composed of heterogeneous transceivers. More specifically, we construct a game-theoretic model for joint spectrum and power allocation, and it is proved that the model constitutes an exact potential game (EPG) with at least one Nash equilibrium (NE) point. We then design the JSPA-BR algorithm which can converge quickly and approach the global optimal solution. Simulations and measurements show that this method maximizes the use of limited spectrum resources. It also mitigates EMI between transceivers and the external radiation of the system. It achieves electromagnetic compatibility of HUTC, thereby demonstrating the effectiveness and accuracy of the proposed approach.

IEEE Internet of Things JournalVol. 12(15)
Chongqing University (CN), King Saud University (SA), KIIT University (IN), Beihang University (CN)
National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 85%
Air Traffic Management and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.