Pinching-Antenna System Design with LoS Blockage: Does In-Waveguide Attenuation Matter?

TL;DR

This paper investigates the impact of in-waveguide attenuation in pinching-antenna systems, showing that neglecting it often has negligible effects on data rate loss even in large service areas, and proposes an optimization algorithm for multi-user scenarios.

Contribution

It extends analysis of in-waveguide attenuation effects to realistic LoS blockage scenarios and introduces a dynamic SAA algorithm for optimizing multi-user pinching-antenna systems.

Findings

In-waveguide attenuation neglect causes negligible data rate loss under typical LoS blockage.

The proposed SAA algorithm effectively maximizes sum rate in multi-user environments.

Simulation results show significant performance gains in blocked LoS conditions.

Abstract

In the literature of pinching-antenna systems, in-waveguide attenuation is often neglected to simplify system design and enable more tractable analysis. However, its effect on overall system performance has received limited attention in the existing literature. While a recent study has shown that, in line-of-sight (LoS)-dominated environments, the data rate loss incurred by omitting in-waveguide attenuation is negligible when the communication area is not excessively large, its effect under more general conditions remains unclear. This work extends the analysis to more realistic scenarios involving arbitrary levels of LoS blockage. We begin by examining a single-user case and derive an explicit expression for the average data rate loss caused by neglecting in-waveguide attenuation. The results demonstrate that, even for large service areas, the rate loss remains negligible under typical LoS blockage conditions. We then consider a more general multi-user scenario, where multiple pinching antennas, each deployed on a separate waveguide, jointly serve multiple users. The objective is to maximize the average sum rate by jointly optimize antenna positions and transmit beamformers to maximize the average sum rate under probabilistic LoS blockage. To solve the resulting stochastic and nonconvex optimization problem, we propose a dynamic sample average approximation (SAA) algorithm. At each iteration, this method replaces the expected objective with an empirical average computed from dynamically regenerated random channel realizations, ensuring that the optimization accurately reflects the current antenna configuration. Extensive simulation results are provided to the proposed algorithm and demonstrate the substantial performance gains of pinching-antenna systems, particularly in environments with significant LoS blockage.