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Latency-Constrained Resource Synergization for Mission-Oriented 6G Non-Terrestrial Networks

Yueshan Lin, Wei Feng, Yunfei Chen, Yongxu Zhu, Ning Ge, Shi Jin

Abstract

This paper investigates latency-constrained resource synergization for mission-oriented non-terrestrial networks (NTNs) in post-disaster emergency scenarios. When terrestrial infrastructures are damaged, unmanned aerial vehicles (UAVs) equipped with edge information hubs (EIHs) are deployed to provide temporary coverage and synergize communication and computing resources for rapid situation awareness. We formulate a joint resource configuration and location optimization problem to minimize overall resource costs while guaranteeing stringent latency requirements. Through analytical derivations, we obtain closed-form optimal solutions that reveal the fundamental tradeoff between communication and computing resources, and develop a successive convex approximation method for EIH location optimization. Simulation results demonstrate that the proposed scheme achieves approximately 20% cost reduction compared with benchmark approaches, validating its optimality and effectiveness for mission-critical emergency response applications in the sixth-generation (6G) era.

Latency-Constrained Resource Synergization for Mission-Oriented 6G Non-Terrestrial Networks

Abstract

This paper investigates latency-constrained resource synergization for mission-oriented non-terrestrial networks (NTNs) in post-disaster emergency scenarios. When terrestrial infrastructures are damaged, unmanned aerial vehicles (UAVs) equipped with edge information hubs (EIHs) are deployed to provide temporary coverage and synergize communication and computing resources for rapid situation awareness. We formulate a joint resource configuration and location optimization problem to minimize overall resource costs while guaranteeing stringent latency requirements. Through analytical derivations, we obtain closed-form optimal solutions that reveal the fundamental tradeoff between communication and computing resources, and develop a successive convex approximation method for EIH location optimization. Simulation results demonstrate that the proposed scheme achieves approximately 20% cost reduction compared with benchmark approaches, validating its optimality and effectiveness for mission-critical emergency response applications in the sixth-generation (6G) era.
Paper Structure (14 sections, 6 theorems, 55 equations, 9 figures, 4 tables, 1 algorithm)

This paper contains 14 sections, 6 theorems, 55 equations, 9 figures, 4 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related Works
  3. System Model
  4. Problem Formulation and Proposed Solution
  5. Problem Formulation
  6. Optimal Configuration of Communication and Computing Resources
  7. Optimal location of the EIH
  8. Simulation Results
  9. Conclusion
  10. Proof of Theorem \ref{['theo 0']}
  11. Proof of Theorem \ref{['theo 2']}
  12. Proof of Theorem \ref{['theorem B opt']}
  13. Proof of Theorem \ref{['theorem R^S F opt']}
  14. Proof of Theorem \ref{['theo placement prob equiv']}

Key Result

Theorem 1

Assume that the values of variables $B_u$, $R_u^S$ and $F_u$ are given, there exists an optimal value of variable $\eta_u^{\mathrm{opt}} = \eta_u^{\mathrm{opt}}(B_u,R_u^S,F_u)$ so that inequalities and hold, where the expressions of $\eta_u^{\mathrm{opt}}$, $T_u^{\eta-\mathrm{opt}}(B_u,R_u^S,F_u)$ and $V_u^{\eta-\mathrm{opt}}(B_u,R_u^S,F_u)$ are given in Table T_u V_u eta_opt.

Figures (9)

  • Figure 1: EIH-empowered non-terrestrial network used for sensing data uploading in disaster areas.
  • Figure 2: Data flow diagram of the EIH during the data uploading process.
  • Figure 3: Relationship between the overall latency and the UAV-satellite transmission bandwidth.
  • Figure 4: Relationship between the data offloading time and the configured to-satellite data rate $R_{\rm total}^S$ and CPU frequency $F_{\rm total}$, under four different to-user communication bandwidth configurations: (a) $B_{\rm total} = 0.3$ MHz; (b) $B_{\rm total} = 0.5$ MHz; (c) $B_{\rm total} = 0.676$ MHz (optimal configuration $B_{\rm total}^*$); (d) $B_{\rm total} = 1.2$ MHz.
  • Figure 5: Relationship between the data offloading time and the configured to-satellite data rate $R_{\rm total}^S$, with given CPU frequency $F_{\rm total}$ and varying to-user communication bandwidth $B_{\rm total}$.
  • ...and 4 more figures

Theorems & Definitions (12)

  • Theorem 1
  • proof : Proof:
  • Theorem 2
  • proof : Proof:
  • Theorem 3
  • proof : Proof:
  • Theorem 4
  • proof : Proof:
  • Theorem 5
  • proof : Proof:
  • ...and 2 more