Volume 23, Issue 2 (JIAEEE Vol.23 No.2 2026)
Journal of Iranian Association of Electrical and Electronics Engineers 2026, 23(2): 19-28 |
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Hayatolgheybi H, Kuhestani A, Keshavarzi M. Intelligent Resource Allocation in Wireless Communication Systems Based on deep Neural Networks. Journal of Iranian Association of Electrical and Electronics Engineers 2026; 23 (2) :19-28
URL: http://jiaeee.com/article-1-1729-en.html
URL: http://jiaeee.com/article-1-1729-en.html
Department of Electrical and Computer Engineering, Qom University of Technology
Abstract: (54 Views)
5G networks are designed to provide higher data rates, lower energy consumption and very short latency. Resource allocation (RA) in wireless communication systems is an intelligent process to allocate the limited resources available in different blocks of these systems in order to meet the needs of end users. In contrast to traditional approaches in which the optimal strategy for RA is determined based on analytical models and using a set of assumptions, the method based on deep neural networks can rely on its ability to adapt to the environment directly from real channel data to achieve use the optimal strategy and provide superior performance in practice. In this paper, an intelligent scheme based on deep neural networks is presented for RA in 5G networks, which includes user-to-base station (CUE) cellular communication and D2D communication between users. In this plan, by considering the non-ideal system model, we achieve the dedicated resources (Maximum Production Efficiency (Max SE), Energy Efficiency (Max EE) and Minimum Transmission Power Min PW)) with interference constraints, QoS and minimum transmission power. Uses non-ideal.
Keywords: Wireless communication systems (WCS), resource allocation (RA), deep neural networks (DNN), denoising auto encryption network (DAE).
Type of Article: Research |
Subject:
Communication
Received: 2024/06/8 | Accepted: 2025/12/6 | Published: 2026/06/22
Received: 2024/06/8 | Accepted: 2025/12/6 | Published: 2026/06/22
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