Fluid-antenna-aided SWIPT UAV–NOMA relaying: Analysis and deployment
AEU - International Journal of Electronics and Communications, cilt.218, 2027 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 218
- Basım Tarihi: 2027
- Doi Numarası: 10.1016/j.aeue.2026.156647
- Dergi Adı: AEU - International Journal of Electronics and Communications
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Compendex, INSPEC, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO), Technology Collection (ProQuest)
- Anahtar Kelimeler: Amplify-and-forward relaying, Fluid antenna systems, Nonorthogonal multiple access, Outage probability, Simultaneous wireless information and power transfer, Unmanned aerial vehicle deployment
- İstanbul Gelişim Üniversitesi Adresli: Evet
Özet
This paper develops an outage-analysis and deployment framework for a power-splitting simultaneous wireless information and power transfer (SWIPT)-enabled unmanned aerial vehicle (UAV) relay serving multiple fluid-antenna users through half-duplex variable-gain amplify-and-forward nonorthogonal multiple access (NOMA) relaying. The instantaneous relay gain is derived from the harvested-energy constraint. Under the exact relay gain, each layer-decoding condition is transformed into a selected-gain-dependent threshold on the base-station–UAV channel, yielding an exact one-dimensional outage integral for an arbitrary distribution of the selected fluid-antenna gain. A relay-input signal-to-noise ratio (SNR) approximation then produces tractable correlated-port outage representations and an independent-port closed-form expression. Spatial dependence is modeled using a Gaussian copula calibrated to the power-gain correlation induced by a physical complex-channel model. The asymptotic analysis establishes diversity order one under a finite inverse-moment condition and separately characterizes the logarithmically modified single-port behavior. For deployment, a globally optimal bounded weighted-centroid benchmark is derived for a convex geometric surrogate, and a data-driven initializer validated using the exact outage objective is developed. The baseline derivations assume Rayleigh fading, linear energy harvesting, perfect channel state information, ideal successive interference cancellation, and a predetermined decoding order. Their robustness is numerically assessed under Rician fading, a sensitivity-and-saturation nonlinear energy-harvesting model, aged port-selection channel state information, residual successive interference cancellation, and instantaneous order adaptation. The proposed placement initializer is also compared with random-forest and multilayer-perceptron alternatives.