Beyond diagonal-IRS assisted UAVs in terahertz network utilizing twin-delayed deep deterministic policy gradient approach

Shereen S. Omar (), Ahmed M. Abd EL-Haleem, Ibrahim I. Ibrahim and Amany M. Saleh
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Shereen S. Omar: Helwan University
Ahmed M. Abd EL-Haleem: Helwan University
Ibrahim I. Ibrahim: Helwan University
Amany M. Saleh: Helwan University

Telecommunication Systems: Modelling, Analysis, Design and Management, 2025, vol. 88, issue 2, No 18, 20 pages

Abstract: Abstract This paper presents an innovative approach in Terahertz (THz) band communications in 6G network, utilizing the integration of a Beyond Diagonal Intelligent Reflective Surface (BD-IRS) and Unmanned Aerial Vehicle (UAV) communications. This work examines the significance of THz downlink communication system in achieving an optimal trade-off between system performance and the circuit topology complexity of BD-IRS. An optimization framework named a (BD-IRS UAV) that optimizes the beyond diagonal BD-IRS phase shift in the reflective mode and finds the optimal UAVs locations, aiming to maximize the system data rate has been proposed. The multi BD-IRS UAV formulated problem is modeled as a Markov Decision Process. Nevertheless, this optimization problem is a non-convex and it is difficult to solve optimally. To tackle this difficulty, a Deep Reinforcement Learning based framework utilizing Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm is proposed to achieve an efficient solution. Finally, simulation results demonstrate the emphasis for the proposed robust algorithm-assisted THz system which significantly improves the system data rate and impacts on performance of the system when compared with the benchmark approaches.

Keywords: 6G network; THz network; BD-IRS; UAVs; Outage probability; DRL; TD3 algorithm (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11235-025-01283-1

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