Joint Beamforming for NOMA Assisted Pinching Antenna Systems (PASS)

2025-06-03

AI Summary

This paper addresses the downlink multi-user multiple-input multiple-output (MU-MIMO) system by proposing a NOMA-enhanced Programmable Antenna Sub-Array System (PASS), jointly optimizing transmit beamforming, programmable beamforming, and power allocation to minimize total transmit power. Methodologically, it innovatively integrates NOMA-based power-domain multiple access with a reconfigurable sub-array antenna architecture, overcoming the conventional limitation of beamforming that only adjusts phase or amplitude. A dual-path optimization framework is designed: (i) a gradient-based method leveraging the Majorization-Minimization Primal-Dual Decomposition (MM-PDD) technique, and (ii) a Particle Swarm Optimization (PSO) algorithm incorporating Zero-Forcing (ZF) precoding. Experimental results demonstrate that the proposed PASS reduces total transmit power by up to 95.22% compared to conventional massive MIMO-NOMA systems. Moreover, the PSO-ZF algorithm exhibits robust convergence and superior global search capability, effectively avoiding local optima and outperforming MM-PDD in practical performance.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Pinching antenna system (PASS) configures the positions of pinching antennas (PAs) along dielectric waveguides to change both large-scale fading and small-scale scattering, which is known as pinching beamforming. A novel non-orthogonal multiple access (NOMA) assisted PASS framework is proposed for downlink multi-user multiple-input multiple-output (MIMO) communications. The transmit power minimization problem is formulated to jointly optimize the transmit beamforming, pinching beamforming, and power allocation. To solve this highly nonconvex problem, both gradient-based and swarm-based optimization methods are developed. 1) For gradient-based method, a majorization-minimization and penalty dual decomposition (MM-PDD) algorithm is developed. The Lipschitz gradient surrogate function is constructed based on MM to tackle the nonconvex terms of this problem. Then, the joint optimization problem is decomposed into subproblems that are alternatively optimized based on PDD to obtain stationary closed-form solutions. 2) For swarm-based method, a fast-convergent particle swarm optimization and zero forcing (PSO-ZF) algorithm is proposed. Specifically, the PA position-seeking particles are constructed to explore high-quality pinching beamforming solutions. Moreover, ZF-based transmit beamforming is utilized by each particle for fast fitness function evaluation. Simulation results demonstrate that: i) The proposed NOMA assisted PASS and algorithms outperforms the conventional NOMA assisted massive antenna system. The proposed framework reduces over 95.22% transmit power compared to conventional massive MIMO-NOMA systems. ii) Swarm-based optimization outperforms gradient-based optimization by searching effective solution subspace to avoid stuck in undesirable local optima.

Problem

• Optimize joint beamforming in NOMA-assisted PASS for MIMO.
• Minimize transmit power via gradient and swarm methods.
• Enhance performance over conventional massive MIMO-NOMA systems.

Innovation

• NOMA assisted PASS for MIMO communications
• MM-PDD algorithm for nonconvex optimization
• PSO-ZF algorithm for swarm-based optimization