Efficient Resource Allocation and User Association in NOMA-Enabled Vehicular-Aided HetNets with High Altitude Platforms

The increasing demand for massive connectivity and high data rates has made the efficient use of existing spectrum resources an increasingly challenging problem. Non-orthogonal multiple access (NOMA) is a potential solution for future heterogeneous networks (HetNets) due to its high capacity and spe...

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Hauptverfasser: Nauman, Ali, Maashi, Mashael, Alkahtani, Hend K, Al-Wesabi, Fahd N, Aljehane, Nojood O, Assiri, Mohammed, Ibrahim, Sara Saadeldeen, Khan, Wali Ullah
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creator Nauman, Ali
Maashi, Mashael
Alkahtani, Hend K
Al-Wesabi, Fahd N
Aljehane, Nojood O
Assiri, Mohammed
Ibrahim, Sara Saadeldeen
Khan, Wali Ullah
description The increasing demand for massive connectivity and high data rates has made the efficient use of existing spectrum resources an increasingly challenging problem. Non-orthogonal multiple access (NOMA) is a potential solution for future heterogeneous networks (HetNets) due to its high capacity and spectrum efficiency. In this study, we analyze an uplink NOMA-enabled vehicular-aided HetNet, where multiple vehicular user equipment (VUEs) share the access link spectrum, and a high-altitude platform (HAP) communicates with roadside units (RSUs) through a backhaul communication link. We propose an improved algorithm for user association that selects VUEs for HAPs based on channel coefficient ratios and terrestrial VUEs based on a caching-state backhaul communication link. The joint optimization problems aim to maximize a utility function that considers VUE transmission rates and cross-tier interference while meeting the constraints of backhaul transmission rates and QoS requirements of each VUE. The joint resource allocation optimization problem consists of three sub-problems: bandwidth allocation, user association, and transmission power allocation. We derive a closed-form solution for bandwidth allocation and solve the transmission power allocation sub-problem iteratively using Taylor expansion to transform a non-convex term into a convex one. Our proposed three-stage iterative algorithm for resource allocation integrates all three sub-problems and is shown to be effective through simulation results. Specifically, the results demonstrate that our solution achieves performance improvements over existing approaches.
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