Joint Beamforming Design and Resource Allocation for IRS-Assisted Full-Duplex Terahertz Systems
Chi Qiu, Wen Chen, Qingqing Wu, Fen Hou, Wanming Hao, Ruiqi Liu, Derrick Wing Kwan Ng

TL;DR
This paper develops a joint beamforming and resource allocation framework for IRS-assisted full-duplex terahertz systems, addressing propagation challenges and residual interference to improve spectral efficiency and fairness.
Contribution
It introduces a novel joint optimization framework for IRS phase shifts, power control, and bandwidth allocation tailored to THz channel characteristics and residual SI.
Findings
Proposed algorithms outperform benchmarks in spectral efficiency.
Joint optimization enhances fairness among users.
Adaptive bandwidth allocation further improves system performance.
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,…
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