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.

翻译：智能反射表面辅助的全双工太赫兹通信系统已成为满足未来无线网络对超高数据速率和频谱效率日益增长需求的前瞻性范式。然而，此类系统的实际部署面临独特的技术挑战，这些挑战源于太赫兹频段严重的传播损耗、频率相关的分子吸收效应，以及全双工通信固有的强残余自干扰。为解决这些问题，本文提出了一种联合资源分配框架，旨在最大化所有用户中的加权最小速率，从而保障服务质量公平性。具体而言，所提设计联合优化IRS反射相位、上下行发射功率控制、子带带宽分配及子带分配方案，并显式建模了太赫兹信道的独特传播特性与残余自干扰的影响。为权衡系统性能与计算复杂度，本文在两种频谱划分方案下开发了计算高效的算法：一种采用等宽子带分配以简化优化问题求解，另一种引入自适应带宽分配以进一步提升频谱利用率和系统灵活性。仿真结果验证了所提设计的有效性，并表明所采用的方案相较于基准方案实现了显著的频谱效率提升。