Energy Efficient User Clustering, Hybrid Precoding and Power Optimization in Terahertz MIMO-NOMA Systems

TL;DR

This paper introduces a novel energy efficiency maximization framework for THz-NOMA-MIMO systems, employing machine learning-based user clustering, hybrid precoding, and distributed power optimization, demonstrating improved performance and lower power consumption.

Contribution

It presents the first comprehensive energy efficiency optimization approach for THz-NOMA-MIMO systems, integrating machine learning, hybrid precoding, and distributed power allocation methods.

Findings

Faster convergence and higher EE with the proposed user clustering scheme.

Lower power consumption achieved through hybrid precoding design.

Enhanced EE in cache-enabled THz-NOMA networks with power optimization.

Abstract

Terahertz (THz) band communication has been widely studied to meet the future demand for ultra-high capacity. In addition, multi-input multi-output (MIMO) technique and non-orthogonal multiple access (NOMA) technique with multi-antenna also enable the network to carry more users and provide multiplexing gain. In this paper, we study the maximization of energy efficiency (EE) problem in THz-NOMA-MIMO systems for the first time. And the original optimization problem is divided into user clustering, hybrid precoding and power optimization. Based on channel correlation characteristics, a fast convergence scheme for user clustering in THz-NOMA-MIMO system using enhanced K-means machine learning algorithm is proposed. Considering the power consumption and implementation complexity, the hybrid precoding scheme based on the sub-connection structure is adopted. Considering the fronthaul link capacity constraint, we design a distributed alternating direction method of multipliers (ADMM) algorithm for power allocation to maximize the EE of THz-NOMA cache-enabled system with imperfect successive interference cancellation (SIC). The simulation results show that the proposed user clustering scheme can achieve faster convergence and higher EE, the design of the hybrid precoding of the sub-connection structure can achieve lower power consumption and power optimization can achieve a higher EE for the THz cache-enabled network.