Shah, Syed (2024) CR-Enabled NOMA Integrated Non-Terrestrial IoT Networks with Transmissive RIS. In: IEEE Global Communications Conference, 2024-12-08 - 2024-12-12, Cape Town, South Africa.
Shah, Syed (2024) CR-Enabled NOMA Integrated Non-Terrestrial IoT Networks with Transmissive RIS. In: IEEE Global Communications Conference, 2024-12-08 - 2024-12-12, Cape Town, South Africa.
Shah, Syed (2024) CR-Enabled NOMA Integrated Non-Terrestrial IoT Networks with Transmissive RIS. In: IEEE Global Communications Conference, 2024-12-08 - 2024-12-12, Cape Town, South Africa.
Abstract
This work proposes a transmissive reconfigurable intelligent surface (T-RIS)-equipped low earth orbit (LEO) satellite communication in cognitive radio-enabled integrated non-terrestrial networks (NTNs). In the proposed system, a geostationary (GEO) satellite operates as a primary network, and a T-RIS-equipped LEO satellite operates as a secondary Internet of Things (IoT) network. The objective is to maximize the sum rate of T-RIS-equipped LEO satellite communication using downlink non-orthogonal multiple access (NOMA) while ensuring the service quality of GEO cellular users. Our framework simultaneously optimizes the total transmit power of LEO, NOMA power allocation for LEO IoT (LIoT) and T-RIS phase shift design subject to the service quality of LIoT and interference temperature to the primary GEO network. To solve the nonconvex sum rate maximization problem, we first adopt successive convex approximations to reduce the complexity of the formulated optimization. Then, we divide the problem into two parts, i.e., power allocation of LEO and phase shift design of T-RIS. The power allocation problem is solved using Karush–Kuhn–Tucker conditions, while the phase shift problem is handled by Taylor approximation and semidefinite programming. Numerical results are provided to validate the proposed optimization framework.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: _not provided_ |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 02 Oct 2024 08:09 |
Last Modified: | 02 Oct 2024 08:09 |
URI: | http://repository.essex.ac.uk/id/eprint/39239 |
Available files
Filename: m60014-khan final.pdf