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Latency Minimization for IRS-enhanced Wideband MEC Networks with Practical Reflection Model

N. Li, W. Hao, X. Li, Z. Zhu, Z. Tang, S. Yang

TL;DR

This work tackles latency minimization in an IRS-enhanced wideband MEC system under a practical non-ideal reflection model. It proposes a block coordinate descent framework that alternates between computing-resource optimization (offloading data and edge allocation) and communication-resource optimization (BS receiving vectors and IRS phase shifts) using Lagrangian dual reformulations and MSE-based equivalences. The approach yields fast convergence and shows latency improvements over ideal-IRS benchmarks, underscoring the importance of realistic IRS modeling in wideband MEC settings. Practically, the method provides a tractable, effective means to balance local versus edge computation and to steer passive beamforming for enhanced offloading in broadband scenarios.

Abstract

Intelligent reflecting surface (IRS) has been considered as an efficient way to boost the computation capability of mobile edge computing (MEC) system, especially when the communication links is blocked or the communication signal is weak. However, most existing works are restricted to narrow-band channel and ideal IRS reflection model, which is not practical and may lead to significant performance degradation in realistic systems. To further exploit the benefits of IRS in MEC system, we consider an IRS-enhanced wideband MEC system with practical IRS reflection model. With the aim of minimizing the weighted latency of all devices, the offloading data volume, edge computing resource, BS's receiving vector, and IRS passive beamforming are jointly optimized. Since the formulated problem is non-convex, we employ the block coordinate descent (BCD) technique to decouple it into two subproblems for alternatively optimizing computing and communication settings. The effectiveness and convergence of the proposed algorithm are validate via numerical analyses. In addition, simulation results demonstrate that the proposed algorithm can achieve lower latency compared to that based on the ideal IRS reflection model, which confirms the necessary of considering practical model when designing an IRS-enhanced wideband MEC system.

Latency Minimization for IRS-enhanced Wideband MEC Networks with Practical Reflection Model

TL;DR

This work tackles latency minimization in an IRS-enhanced wideband MEC system under a practical non-ideal reflection model. It proposes a block coordinate descent framework that alternates between computing-resource optimization (offloading data and edge allocation) and communication-resource optimization (BS receiving vectors and IRS phase shifts) using Lagrangian dual reformulations and MSE-based equivalences. The approach yields fast convergence and shows latency improvements over ideal-IRS benchmarks, underscoring the importance of realistic IRS modeling in wideband MEC settings. Practically, the method provides a tractable, effective means to balance local versus edge computation and to steer passive beamforming for enhanced offloading in broadband scenarios.

Abstract

Intelligent reflecting surface (IRS) has been considered as an efficient way to boost the computation capability of mobile edge computing (MEC) system, especially when the communication links is blocked or the communication signal is weak. However, most existing works are restricted to narrow-band channel and ideal IRS reflection model, which is not practical and may lead to significant performance degradation in realistic systems. To further exploit the benefits of IRS in MEC system, we consider an IRS-enhanced wideband MEC system with practical IRS reflection model. With the aim of minimizing the weighted latency of all devices, the offloading data volume, edge computing resource, BS's receiving vector, and IRS passive beamforming are jointly optimized. Since the formulated problem is non-convex, we employ the block coordinate descent (BCD) technique to decouple it into two subproblems for alternatively optimizing computing and communication settings. The effectiveness and convergence of the proposed algorithm are validate via numerical analyses. In addition, simulation results demonstrate that the proposed algorithm can achieve lower latency compared to that based on the ideal IRS reflection model, which confirms the necessary of considering practical model when designing an IRS-enhanced wideband MEC system.
Paper Structure (17 sections, 51 equations, 9 figures, 2 tables, 3 algorithms)

This paper contains 17 sections, 51 equations, 9 figures, 2 tables, 3 algorithms.

Table of Contents

  1. Introduction
  2. Prior Works
  3. MEC system
  4. IRS-enhanced MEC systems
  5. Motivations and contributions
  6. System Model and Problem Formulation
  7. System Model
  8. IRS Reflection Model
  9. Communication Model
  10. Computing Model
  11. Problem Formulation
  12. Proposed Solution Based on BCD Technique
  13. Optimization of Offloading Data Volume and Edge Computing Resources
  14. Joint Optimization of BS's Receiving Vector and IRS BPS
  15. Complexity Analysis of Algorithm 2
  16. ...and 2 more sections

Figures (9)

  • Figure 1: IRS-enhanced wideband MEC system model.
  • Figure 2: The simulation scenario setup.
  • Figure 3: Convergence hehavior of the proposed algorithm
  • Figure 4: Latency versus the resolution $b$.
  • Figure 5: Latency versus the number of transmit antennas $M$.
  • ...and 4 more figures