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User-UAV Association for Dynamic User in mmWave Communication for eMBB and URLLC

Siddhanta Parial, Sasthi C. Ghosh, Anil K. Ghosh

TL;DR

This work tackles dynamic user-UAV association in mmWave networks supporting mixed traffic types by accounting for user mobility within a time interval and traffic-specific LoS requirements. It develops analytical expressions for $eMBB$ LoS area and $URLLC$ LoS radius, and introduces a shadow polygon geometric approach to compute these metrics under building blockages. An association policy assigns each user to the UAV offering the maximum average throughput for $eMBB$ or the maximum $URLLC$ LoS radius for $URLLC$, using either analytical or shadow polygon based LoS metrics. Simulations show the shadow polygon method closely matches the analytical results and significantly outperforms discretization and existing max-throughput policies, highlighting improved robustness to mobility and urban blockage in UAV-assisted mmWave networks.

Abstract

In unmanned aerial vehicle (UAV) assisted millimeter wave (mmWave) communication, appropriate user-UAV association is crucial for improving system performance. In mmWave communication, user throughput largely depends on the line of sight (LoS) connectivity with the UAV, which in turn depends on the mobility pattern of the users. Moreover, different traffic types like enhanced mobile broadband (eMBB) and ultra reliable low latency communication (URLLC) may require different types of LoS connectivity. Existing user-UAV association policies do not consider the user mobility during a time interval and different LoS requirements of different traffic types. In this paper, we consider both of them and develop a user association policy in the presence of building blockages. First, considering a simplified scenario, we have analytically established the LoS area, which is the region where users will experience seamless LoS connectivity for eMBB traffic, and the LoS radius, which is the radius of the largest circle within which the user gets uninterrupted LoS services for URLLC traffic. Then, for a more complex scenario, we present a geometric shadow polygon-based method to compute LoS area and LoS radius. Finally, we associate eMBB and URLLC users, with the UAVs from which they get the maximum average throughput based on LoS area and maximum LoS radius respectively. We show that our approach outperforms the existing discretization based and maximum throughput based approaches.

User-UAV Association for Dynamic User in mmWave Communication for eMBB and URLLC

TL;DR

This work tackles dynamic user-UAV association in mmWave networks supporting mixed traffic types by accounting for user mobility within a time interval and traffic-specific LoS requirements. It develops analytical expressions for LoS area and LoS radius, and introduces a shadow polygon geometric approach to compute these metrics under building blockages. An association policy assigns each user to the UAV offering the maximum average throughput for or the maximum LoS radius for , using either analytical or shadow polygon based LoS metrics. Simulations show the shadow polygon method closely matches the analytical results and significantly outperforms discretization and existing max-throughput policies, highlighting improved robustness to mobility and urban blockage in UAV-assisted mmWave networks.

Abstract

In unmanned aerial vehicle (UAV) assisted millimeter wave (mmWave) communication, appropriate user-UAV association is crucial for improving system performance. In mmWave communication, user throughput largely depends on the line of sight (LoS) connectivity with the UAV, which in turn depends on the mobility pattern of the users. Moreover, different traffic types like enhanced mobile broadband (eMBB) and ultra reliable low latency communication (URLLC) may require different types of LoS connectivity. Existing user-UAV association policies do not consider the user mobility during a time interval and different LoS requirements of different traffic types. In this paper, we consider both of them and develop a user association policy in the presence of building blockages. First, considering a simplified scenario, we have analytically established the LoS area, which is the region where users will experience seamless LoS connectivity for eMBB traffic, and the LoS radius, which is the radius of the largest circle within which the user gets uninterrupted LoS services for URLLC traffic. Then, for a more complex scenario, we present a geometric shadow polygon-based method to compute LoS area and LoS radius. Finally, we associate eMBB and URLLC users, with the UAVs from which they get the maximum average throughput based on LoS area and maximum LoS radius respectively. We show that our approach outperforms the existing discretization based and maximum throughput based approaches.

Paper Structure

This paper contains 18 sections, 3 theorems, 15 equations, 3 figures, 1 table, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. User Mobility Model
  4. Blockage Model
  5. Communication Model
  6. User Traffic
  7. Analytical Approach
  8. eMBB LoS Area Calculation
  9. URLLC LoS Radius Calculation
  10. Shadow Polygon Approach
  11. Preprocessing
  12. Computation of eMBB LoS Area
  13. Computation of URLLC LoS Radius
  14. UAV Association Policy
  15. Association for eMBB User
  16. ...and 3 more sections

Key Result

Lemma 1

The eMBB LoS area $\Delta_k$ is $\min\{\frac{2\pi e^{-\frac{\tau}{\xi^k}}}{\left(\frac{\zeta}{\xi^k}\right)^2},\pi R^2_g\}$.

Figures (3)

  • Figure 1: (a) LoS for URLLC and eMBB (b) LoS Blockage
  • Figure 2: (a) Building density vs eMBB area for $a=0.5$, (b) Resolution vs time and relative difference of eMBB area, (c) Building density vs URLLC radius for $a=0.5$, (d) Resolution vs time and relative difference of URLLC radius
  • Figure 3: UAVs vs (a) eMBB throughput (b) URLLC radius

Theorems & Definitions (6)

  • Lemma 1
  • proof
  • Lemma 2
  • proof
  • Lemma 3
  • proof