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Outage Analysis of Aerial Semi-Grant-Free NOMA Systems

Hongjiang Lei, Chen Zhu, Ki-Hong Park, Imran Shafique Ansari, Weijia Lei, Hong Tang, Kyeong Jin Kim

TL;DR

This work analyzes the outage performance of a UAV-enabled downlink NOMA system using semi-grant-free (SGF) transmission and introduces a hybrid successive interference cancellation (SIC) scheme for GB and GF users. It derives exact and asymptotic outage probabilities for the GF user under fixed power allocation and identifies diversity-order conditions, revealing no-zero diversity unless QoS thresholds align favorably. A dynamic power allocation (DPA) scheme is proposed to remove outage floors, with exact and asymptotic OP expressions for the GF user and validation via Monte Carlo simulation. The results show that UAV location and altitude significantly affect GF OP, and there is an optimal 3D placement that depends on the environment, highlighting the practical benefits of SGF NOMA with DPA for UAV-assisted connectivity.

Abstract

In this paper, we analyze the outage performance of unmanned aerial vehicles (UAVs)-enabled downlink non-orthogonal multiple access (NOMA) communication systems with the semi-grant-free (SGF) transmission scheme. A UAV provides coverage services for a grant-based (GB) user and one user is allowed to utilize the same channel resource opportunistically. The hybrid successive interference cancellation scheme is implemented in the downlink NOMA scenarios for the first time. The analytical expressions for the exact and asymptotic outage probability (OP) of the grant-free (GF) user are derived. The results demonstrate that no-zero diversity order can be achieved only under stringent conditions on users' quality of service requirements. Subsequently, we propose an efficient dynamic power allocation (DPA) scheme to relax such data rate constraints to address this issue. The analytical expressions for the exact and asymptotic OP of the GF user with the DPA scheme are derived. Finally, Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of the UAV's location and altitude on the OP of the GF user.

Outage Analysis of Aerial Semi-Grant-Free NOMA Systems

TL;DR

This work analyzes the outage performance of a UAV-enabled downlink NOMA system using semi-grant-free (SGF) transmission and introduces a hybrid successive interference cancellation (SIC) scheme for GB and GF users. It derives exact and asymptotic outage probabilities for the GF user under fixed power allocation and identifies diversity-order conditions, revealing no-zero diversity unless QoS thresholds align favorably. A dynamic power allocation (DPA) scheme is proposed to remove outage floors, with exact and asymptotic OP expressions for the GF user and validation via Monte Carlo simulation. The results show that UAV location and altitude significantly affect GF OP, and there is an optimal 3D placement that depends on the environment, highlighting the practical benefits of SGF NOMA with DPA for UAV-assisted connectivity.

Abstract

In this paper, we analyze the outage performance of unmanned aerial vehicles (UAVs)-enabled downlink non-orthogonal multiple access (NOMA) communication systems with the semi-grant-free (SGF) transmission scheme. A UAV provides coverage services for a grant-based (GB) user and one user is allowed to utilize the same channel resource opportunistically. The hybrid successive interference cancellation scheme is implemented in the downlink NOMA scenarios for the first time. The analytical expressions for the exact and asymptotic outage probability (OP) of the grant-free (GF) user are derived. The results demonstrate that no-zero diversity order can be achieved only under stringent conditions on users' quality of service requirements. Subsequently, we propose an efficient dynamic power allocation (DPA) scheme to relax such data rate constraints to address this issue. The analytical expressions for the exact and asymptotic OP of the GF user with the DPA scheme are derived. Finally, Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of the UAV's location and altitude on the OP of the GF user.
Paper Structure (17 sections, 4 theorems, 57 equations, 6 figures, 1 table)

This paper contains 17 sections, 4 theorems, 57 equations, 6 figures, 1 table.

Key Result

Theorem 1

The analytical expression for the OP of $D_F$ is expressed as where ${\Theta _{th}} = {2^{R_{{\rm{th}}}^F}}$, ${T_0} = {F_{{G_B}}}\left( {{\varepsilon _1}} \right)$, ${T_{11}} = {\chi _1} - {\chi _2}$, ${T_{12a}} = {\chi _3} + {\chi _4}$, ${T_{12b}} = {{\bar{F}}_{{G_B}}}\left( {{\varepsilon _1}} \right) - {A_1}\sum\limits_{i = 0}^{m - 1} {\frac{{\lambda _F^i\G

Figures (6)

  • Figure 1: A downlink UAV-based NOMA communication system consisting of one UAV ($U$) and two legitimate users (${D_B}$ and ${D_F}$).
  • Figure 2: The effect of UAV's position and $\rho$ on the OP of $D_F$ with ${\Theta _{th}} < 1 + \frac{1}{{{\Theta _B} - 1}}$.
  • Figure 3: The effect of UAV's position and $\rho$ on the OP of $D_F$ with ${\Theta _{th}} > 1 + \frac{1}{{{\Theta _B} - 1}}$.
  • Figure 4: The impact of RRT of $D_B$ and $D_F$ on the OP of $D_F$.
  • Figure 5: The impact of the UAV's position and altitude on the OP of $D_F$ with ${R_{{\rm{th}}}^B} = 0.2$ and ${R_{{\rm{th}}}^F} = 2$.
  • ...and 1 more figures

Theorems & Definitions (8)

  • Remark 1
  • Remark 2
  • Theorem 1
  • Corollary 1
  • Remark 3
  • Theorem 2
  • Corollary 2
  • Remark 4