An EMC-Aware Multi-Objective Framework for Joint Radio-Resource and Transmit-Power Coordination in Ultra-Dense 5G/Beyond-5G Networks

Ultra-dense 5G and beyond-5G networks improve spatial spectrum reuse but intensify co-channel interference, creating coupled challenges in electromagnetic compatibility (EMC), quality of service (QoS), and radio-resource management. This study develops an EMC-aware multi-objective framework for joint radio-resource and transmit-power coordination. Raw link-specific interference thresholds are derived from signal-to-interference-plus-noise-ratio requirements. Non-negative thresholds define physically admissible interference budgets, whereas negative raw thresholds explicitly identify intrinsically SINR-infeasible links. The resulting operational EMC states drive actionable critical-link detection, dominant-interferer localization, bounded resource-block reassignment, and conditional power adaptation. System-level simulations over 100 paired Monte Carlo realizations compare the proposed method with four non-adaptive, learning-based, deterministic joint, and population-based reference schemes under common network and channel conditions. At 80 base stations and 200 user equipment (UEs), the proposed method achieves an EMC score of 0.568 and an EMC violation ratio of 0.419, together with a 13.26 dB mean signal-to-interference-plus-noise ratio, 376.63 Mbit/s aggregate throughput, and 18.83 bit/s/Hz spectral efficiency. Its runtime is 34.08 s per realization, compared with 93.79 s and 476.53 s for the two iterative joint-optimization benchmarks. The results indicate a distinct performance–complexity trade-off rather than universal metric-wise superiority.

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Publication Details

Journal
Journal of Sensor and Actuator Networks
Published
2026-10-14
DOI
https://doi.org/10.3390/jsan15050083
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

An EMC-Aware Multi-Objective Framework for Joint Radio-Resource and Transmit-Power Coordination in Ultra-Dense 5G/Beyond-5G Networks

Amir Lazarev, Mubarak Baltabaevna Abdujapparova, Alpamis Kutlimuratov, Haydar Madaminov et al.
Journal of Sensor and Actuator Networks
Advanced MIMO Systems Optimization
article

An EMC-Aware Multi-Objective Framework for Joint Radio-Resource and Transmit-Power Coordination in Ultra-Dense 5G/Beyond-5G Networks

Amir Lazarev, Mubarak Baltabaevna Abdujapparova, Alpamis Kutlimuratov, Haydar Madaminov, Islambek Saymanov, ХАМИДОВА Нилуфар Джумаваевна, Farxod Nuraliev
article en

Abstract

Ultra-dense 5G and beyond-5G networks improve spatial spectrum reuse but intensify co-channel interference, creating coupled challenges in electromagnetic compatibility (EMC), quality of service (QoS), and radio-resource management. This study develops an EMC-aware multi-objective framework for joint radio-resource and transmit-power coordination. Raw link-specific interference thresholds are derived from signal-to-interference-plus-noise-ratio requirements. Non-negative thresholds define physically admissible interference budgets, whereas negative raw thresholds explicitly identify intrinsically SINR-infeasible links. The resulting operational EMC states drive actionable critical-link detection, dominant-interferer localization, bounded resource-block reassignment, and conditional power adaptation. System-level simulations over 100 paired Monte Carlo realizations compare the proposed method with four non-adaptive, learning-based, deterministic joint, and population-based reference schemes under common network and channel conditions. At 80 base stations and 200 user equipment (UEs), the proposed method achieves an EMC score of 0.568 and an EMC violation ratio of 0.419, together with a 13.26 dB mean signal-to-interference-plus-noise ratio, 376.63 Mbit/s aggregate throughput, and 18.83 bit/s/Hz spectral efficiency. Its runtime is 34.08 s per realization, compared with 93.79 s and 476.53 s for the two iterative joint-optimization benchmarks. The results indicate a distinct performance–complexity trade-off rather than universal metric-wise superiority.

Journal of Sensor and Actuator NetworksVol. 15(5)
Academy of Sciences Republic of Uzbekistan (UZ), Tashkent University of Information Technology (UZ), Tashkent State Technical University named after Islam Karimov (UZ), Kimyo International University in Tashkent (UZ), New Uzbekistan University (UZ), National University of Uzbekistan (UZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Advanced MIMO Systems Optimization
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