Multi-Waveguide Pinching Antenna Placement Optimization for Rate Maximization

TL;DR

This paper presents an optimization framework for antenna placement in multi-waveguide pinching antenna systems to maximize per-user data rates, employing fractional programming and gradient ascent techniques.

Contribution

It introduces a novel optimization approach combining fractional programming and projected gradient ascent for antenna placement in PASS systems, addressing non-convex constraints.

Findings

Proposed scheme outperforms geometric baselines in simulations.

Achieves higher per-user data rates by reducing multi-user interference.

Demonstrates effectiveness of FP and PGA in complex antenna placement problems.

Abstract

Pinching antenna systems (PASS) have emerged as a technology that enables the large-scale movement of antenna elements, offering significant potential for performance gains in next-generation wireless networks. This paper investigates the problem of maximizing the average per-user data rate by optimizing the antenna placement of a multi-waveguide PASS, subject to a stringent physical minimum spacing constraint. To address this complex challenge, which involves a coupled fractional objective and a non-convex constraint, we employ the fractional programming (FP) framework to transform the non-convex rate maximization problem into a more tractable one, and devise a projected gradient ascent (PGA)-based algorithm to iteratively solve the transformed problem. Simulation results demonstrate that our proposed scheme significantly outperforms various geometric placement baselines, achieving superior per-user data rates by actively mitigating multi-user interference.