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Sum-Rate Maximization for NOMA-Assisted Pinching-Antenna Systems

Ziwu Zhou, Zheng Yang, Gaojie Chen, Zhiguo, Ding

TL;DR

This work tackles sum-rate maximization for a downlink NOMA system aided by pinching antennas by jointly optimizing power allocation and antenna placements. It derives a closed-form solution for the power coefficient \alpha_2 via KKT conditions and employs a low-complexity bisection-based search to position the pinching antennas to maximize channel disparity and phase alignment, thereby boosting throughput. The proposed alternating optimization approach demonstrates that pinching antennas significantly outperform conventional fixed antennas in NOMA scenarios, with the placement algorithm closely matching exhaustive search performance. The results highlight the practical potential of reconfigurable pinching-antenna systems for flexible, high-rate wireless communications in dynamic environments.

Abstract

In this letter, we investigate a non-orthogonal multiple access (NOMA) assisted downlink pinching-antenna system. Leveraging the ability of pinching antennas to flexibly adjust users' wireless channel conditions, we formulate an optimization problem to maximize the sum rate by optimizing both the users' power allocation coefficients and the positions of pinching antennas. The optimal power allocation coefficients are obtained in closed-form by using the Karush-Kuhn-Tucker (KKT) conditions. The optimization problem of pinching antenna placements is more challenging than the power allocation problem, and is solved by a bisection-based search algorithm. In particular, the algorithm first optimizes the antenna placements to create favorable channel disparities between users, followed by fine-tuning the antenna positions to ensure the phase alignment for users, thus maximizing the sum rate. Simulation results demonstrate that, compared to conventional-antenna systems, pinching antennas can significantly enhance the sum rate in NOMA scenarios, and the proposed bisection-based search algorithm can achieve a sum rate nearly equivalent to that of an exhaustive search.

Sum-Rate Maximization for NOMA-Assisted Pinching-Antenna Systems

TL;DR

This work tackles sum-rate maximization for a downlink NOMA system aided by pinching antennas by jointly optimizing power allocation and antenna placements. It derives a closed-form solution for the power coefficient \alpha_2 via KKT conditions and employs a low-complexity bisection-based search to position the pinching antennas to maximize channel disparity and phase alignment, thereby boosting throughput. The proposed alternating optimization approach demonstrates that pinching antennas significantly outperform conventional fixed antennas in NOMA scenarios, with the placement algorithm closely matching exhaustive search performance. The results highlight the practical potential of reconfigurable pinching-antenna systems for flexible, high-rate wireless communications in dynamic environments.

Abstract

In this letter, we investigate a non-orthogonal multiple access (NOMA) assisted downlink pinching-antenna system. Leveraging the ability of pinching antennas to flexibly adjust users' wireless channel conditions, we formulate an optimization problem to maximize the sum rate by optimizing both the users' power allocation coefficients and the positions of pinching antennas. The optimal power allocation coefficients are obtained in closed-form by using the Karush-Kuhn-Tucker (KKT) conditions. The optimization problem of pinching antenna placements is more challenging than the power allocation problem, and is solved by a bisection-based search algorithm. In particular, the algorithm first optimizes the antenna placements to create favorable channel disparities between users, followed by fine-tuning the antenna positions to ensure the phase alignment for users, thus maximizing the sum rate. Simulation results demonstrate that, compared to conventional-antenna systems, pinching antennas can significantly enhance the sum rate in NOMA scenarios, and the proposed bisection-based search algorithm can achieve a sum rate nearly equivalent to that of an exhaustive search.

Paper Structure

This paper contains 7 sections, 16 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Problem Formulation and Proposal Solution
  4. Power Allocation Coefficients Optimization
  5. Pinching Antenna Positions Optimization
  6. Simulation Results
  7. conclusion

Figures (4)

  • Figure 1: An illustration of the considered downlink NOMA-assisted pinching-antenna systems.
  • Figure 2: Achievable sum rate of pinching-antenna systems and conventional-antenna systems assisted by NOMA versus transmit power.
  • Figure 3: The effect of different phase alignment accuracies $\delta_1$ and $\delta_2$ on the achievable sum rate of NOMA-assisted pinching-antenna systems.
  • Figure 4: Comparison of the proposed algorithm with the exhaustive search method.