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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Zusammenfassung: | 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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DOI: | 10.48550/arxiv.2401.12141 |