Joint Beamforming Design and Resource Allocation for IRS-Assisted Full-Duplex Terahertz Systems

2025-10-29

AI Summary

To address the three key challenges in terahertz (THz) full-duplex systems—severe propagation loss, frequency-selective molecular absorption, and strong residual self-interference (SI)—this paper proposes an intelligent reflecting surface (IRS)-aided joint beamforming and resource allocation framework. The method jointly optimizes IRS phase shifts, uplink/downlink transmit powers, subband width partitioning, and frequency band assignment to maximize spectral efficiency while ensuring user fairness in quality-of-service. Two computationally efficient algorithms are developed: one supporting fixed subband widths and another enabling adaptive partitioning, balancing implementation complexity and system flexibility. A precise THz channel model incorporating molecular absorption and a realistic SI model are integrated, and the resulting non-convex optimization problem is solved via advanced numerical techniques. Simulation results demonstrate that the proposed scheme significantly outperforms benchmark schemes in both weighted minimum rate and overall spectral efficiency, validating the feasibility and superiority of IRS-enabled THz full-duplex communications.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multi-Robot Systems
• Search and Optimization: Algorithm Configuration

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Security and Privacy: Large-scale security measurements

Abstract

Intelligent reflecting surface (IRS)-assisted full-duplex (FD) terahertz (THz) communication systems have emerged as a promising paradigm to satisfy the escalating demand for ultra-high data rates and spectral efficiency in future wireless networks. However, the practical deployment of such systems presents unique technical challenges, stemming from severe propagation loss, frequency-dependent molecular absorption in the THz band, and the presence of strong residual self-interference (SI) inherent to FD communications. To tackle these issues, this paper proposes a joint resource allocation framework that aims to maximize the weighted minimum rate among all users, thereby ensuring fairness in quality of service. Specifically, the proposed design jointly optimizes IRS reflecting phase shifts, uplink/downlink transmit power control, sub-band bandwidth allocation, and sub-band assignment, explicitly capturing the unique propagation characteristics of THz channels and the impact of residual SI. To strike an balance between system performance and computational complexity, two computationally efficient algorithms are developed under distinct spectrum partitioning schemes: one assumes equal sub-band bandwidth allocation to facilliate tractable optimization, while the other introduces adaptive bandwidth allocation to further enhance spectral utilization and system flexibility. Simulation results validate the effectiveness of the proposed designs and demonstrate that the adopted scheme achieves significant spectral efficiency improvements over benchmark schemes.

Problem

• Optimizing joint beamforming and resource allocation
• Addressing THz propagation loss and self-interference
• Maximizing weighted minimum rate for user fairness

Innovation

• Jointly optimizes IRS phase shifts and power control
• Develops two efficient algorithms for spectrum partitioning
• Adaptive bandwidth allocation enhances spectral utilization