Performance Analysis of RIS-Assisted UAV Communication in NOMA Networks

TL;DR

Addresses outage performance in RIS-assisted BS-UAV downlink NOMA with partitionable RIS. Develops closed-form CDFs for the direct $g^d$, RIS-only indirect $g^r$, and composite $g^c$ links under Nakagami-$m$ and double Nakagami-$m$ fading, enabling tractable outage analysis. Proposes RUOM, a bilevel optimization that merges fair power allocation vector $oldsymbol{eta}$ and minimization of RIS elements $oldsymbol{N_m^k}$ via Progressive Grid Search. Simulations validate the analytical models and show substantial improvements in fairness (max outage reduction across UAVs) and RIS-resource efficiency, underscoring the practical impact for UAV communications in spectrum-constrained networks.

Abstract

This paper investigates the performance of downlink non-orthogonal multiple access (NOMA) communication in unmanned aerial vehicle (UAV) networks enhanced by partitionable reconfigurable intelligent surfaces (RISs). We analyze three types of links between base station (BS) and UAVs: direct, RIS-only indirect, and composite links, under both Line-of-Sight (LoS) and Non-LoS (NLoS) propagation. The RIS-only indirect link and direct link are modeled using double Nakagami-m and Nakagami-m fading, respectively, while the composite link follows a combined fading channel model. Closed-form expressions for the cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived for all links, enabling tractable outage probability analysis. Then, we formulate a fairness-efficiency bilevel optimization problem to minimize the maximum outage probability among UAVs while minimizing the total number of required RIS reflecting elements. Accordingly, an RIS-assisted UAV Outage Minimization (RUOM) algorithm is proposed, which fairly allocates the NOMA power coefficients while minimizing the total number of RIS reflecting elements required, subject to NOMA-defined constraints, RIS resource limitations, and maximum allowable outage threshold. Simulation results validate the analytical models and demonstrate that the proposed RUOM algorithm significantly improves fairness and efficiency in BS-UAV communication.

Figures (4)

• Figure 1: System model consists of three types of links: direct (G2A), RIS-only indirect (G2R2A), and composite (G2A & G2R2A), where a part of RIS elements (the green ones) is assigned to a specific UAV.
• Figure 2: $\mathbb{P}_m^{out}(\boldsymbol{\beta}, N_m^{k^\star})$ vs. various links.
• Figure 3: $\mathbb{P}_m^{out}(\boldsymbol{\beta}, N_m^{k^\star})$ vs. $P_t$.
• Figure 4: $\mathbb{P}_m^{out}(\boldsymbol{\beta}, N_m^{k^\star})$ vs. $R^{tg}$.