Energy-Efficient Resource Allocation for NOMA-Assisted Uplink Pinching-Antenna Systems
Ming Zeng, Xingwang Li, Ji Wang, Gaojian Huang, Octavia A. Dobre, Zhiguo Ding

TL;DR
This paper proposes an energy-efficient resource allocation scheme for NOMA-assisted uplink pinching-antenna systems, jointly optimizing user transmit power and antenna placement to improve energy efficiency over traditional methods.
Contribution
It introduces a novel joint optimization framework for power and antenna positioning in NOMA pinching-antenna systems, employing alternating optimization and particle swarm algorithms.
Findings
Significant EE improvements over conventional antennas.
Outperforms orthogonal multiple access-based pinching-antenna systems.
Effective joint optimization approach for power and antenna placement.
Abstract
The pinching-antenna architecture has emerged as a promising solution for reconfiguring wireless propagation environments and enhancing system performance. While prior research has primarily focused on sum-rate maximization or transmit power minimization of pinching-antenna systems, the critical aspect of energy efficiency (EE) has received limited attention. Given the increasing importance of EE in future wireless communication networks, this work investigates EE optimization in a non-orthogonal multiple access (NOMA)-assisted multi-user pinching-antenna uplink system. The problem entails the joint optimization of the users' transmit power and the pinching-antenna position. The resulting optimization problem is non-convex due to tightly coupled variables. To tackle this, we employ an alternating optimization framework to decompose the original problem into two subproblems: one focusing…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Advanced MIMO Systems Optimization · IoT Networks and Protocols
