Joint Trajectory and Resource Optimization for Dual-aerial ARIS-assisted NOMA-TNT Networks
Vangara Saiprudhvi, Keshav Singh, Hariharan Subramaniyam, Chih-Peng Li

TL;DR
This paper proposes a joint optimization framework for trajectory, beamforming, and ARIS configuration in dual-aerial ARIS-assisted NOMA-ITNTNs, achieving significant sum-rate improvements.
Contribution
It introduces a novel joint optimization approach for dual-aerial ARIS, beamforming, and trajectories in NOMA-based integrated terrestrial and non-terrestrial networks.
Findings
Achieves approximately 8.44% sum-rate improvement over passive RIS.
Proposes a convergent BCD-based algorithm for complex non-convex optimization.
Demonstrates the benefits of dual-aerial ARIS and joint communication-mobility design.
Abstract
Integrated terrestrial and non-terrestrial networks (ITNTNs) are envisioned as a key paradigm for sixth-generation (6G) wireless systems, enabling seamless global connectivity. In this paper, we investigate a dual-aerial active reconfigurable intelligent surface (ARIS)-assisted non-orthogonal multiple access (NOMA)-based ITNTN, where a terrestrial base station (TBS) and a satellite (SAT) simultaneously serve terrestrial and satellite users with the aid of a UAV-mounted ARIS and a HAP-mounted ARIS. Users are multiplexed via power-domain NOMA with a predefined SIC decoding order. We formulate an average sum-rate maximization problem by jointly optimizing transmit beamforming, ARIS coefficients, and the 3D trajectories of the UAV and HAP, subject to power, unit-modulus, ARIS power, and mobility constraints. The problem is highly non-convex due to coupled variables, nonlinear SINR…
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