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Delay Minimization in Pinching-Antenna-enabled NOMA-MEC Networks

Yuan Ai, Xidong Mu, Pengbo Si, Yuanwei Liu

TL;DR

This work introduces a pinching-antenna systems (PASS) enabled uplink NOMA-MEC framework to minimize the maximum task delay across users. It formulates a non-convex joint optimization over offloading ratios, transmit powers, and PA placements, and tackles it with a novel time-equalization transformation that leads to a bisection-search-based alternating optimization (AO) algorithm. The inner AO splits into linear programs for offloading ratios and powers and a multi-resolution, one-dimensional search for PA positions, all guided by feasibility with respect to a common delay target $D_T$. Simulations in a PASS-NOMA-MEC setting show substantial reductions in delay compared with conventional MIMO and OMA baselines, validating the approach for latency-constrained MEC applications.

Abstract

This letter proposes a novel pinching antenna systems (PASS) enabled non-orthogonal multiple access (NOMA) multi-access edge computing (MEC) framework. An optimization problem is formulated to minimize the maximum task delay by optimizing offloading ratios, transmit powers, and pinching antenna (PA) positions, subject to constraints on maximum transmit power, user energy budgets, and minimum PA separation to mitigate coupling effects. To address the non-convex problem, a bisection search-based alternating optimization (AO) algorithm is developed, where each subproblem is iteratively solved for a given task delay. Numerical simulations demonstrate that the proposed framework significantly reduces the task delay compared to benchmark schemes.

Delay Minimization in Pinching-Antenna-enabled NOMA-MEC Networks

TL;DR

This work introduces a pinching-antenna systems (PASS) enabled uplink NOMA-MEC framework to minimize the maximum task delay across users. It formulates a non-convex joint optimization over offloading ratios, transmit powers, and PA placements, and tackles it with a novel time-equalization transformation that leads to a bisection-search-based alternating optimization (AO) algorithm. The inner AO splits into linear programs for offloading ratios and powers and a multi-resolution, one-dimensional search for PA positions, all guided by feasibility with respect to a common delay target . Simulations in a PASS-NOMA-MEC setting show substantial reductions in delay compared with conventional MIMO and OMA baselines, validating the approach for latency-constrained MEC applications.

Abstract

This letter proposes a novel pinching antenna systems (PASS) enabled non-orthogonal multiple access (NOMA) multi-access edge computing (MEC) framework. An optimization problem is formulated to minimize the maximum task delay by optimizing offloading ratios, transmit powers, and pinching antenna (PA) positions, subject to constraints on maximum transmit power, user energy budgets, and minimum PA separation to mitigate coupling effects. To address the non-convex problem, a bisection search-based alternating optimization (AO) algorithm is developed, where each subproblem is iteratively solved for a given task delay. Numerical simulations demonstrate that the proposed framework significantly reduces the task delay compared to benchmark schemes.
Paper Structure (10 sections, 1 theorem, 22 equations, 4 figures, 1 algorithm)

This paper contains 10 sections, 1 theorem, 22 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Problem Formulation
  5. Proposed Solution
  6. Optimizing $\bm{\beta}$
  7. Optimizing $\mathbf{P}$
  8. Optimizing $\mathbf{x}_{\mathrm{p}}$
  9. Simulation Results
  10. Conclusions

Key Result

Lemma 1

In a multi-user NOMA-MEC PASS where all $K$ users offload tasks within a common transmission time $T = T_k^{\text{off}} = T_{k'}^{\text{off}}, \forall k \neq k'$, the offloading time for user $k$ can be equivalently expressed as

Figures (4)

  • Figure 1: Illustration of a PASS-enabled NOMA-MEC framework with single-waveguide.
  • Figure 2: Convergence of the task completion time $D_T$.
  • Figure 3: Task completion time $D_T$ versus number of PAs.
  • Figure 4: Task completion time $D_T$ versus maximum transmit power $P_{\max}$ for task sizes $L_k = 1M\bit$ and $L_k = 1.5M\bit$.

Theorems & Definitions (2)

  • Lemma 1
  • proof