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

TL;DR

This work tackles IRS-assisted full-duplex THz communications under spectrum fragmentation caused by molecular absorption. It formulates a weighted minimum rate (WMR) problem that jointly optimizes IRS phase shifts, UL/DL transmit powers, sub-band bandwidths, and sub-band assignments, under both equal-band and adaptive-band strategies. An ESB solution uses Jensen bounds and a penalty/SCA framework to yield a tractable convex reformulation, while an ASB solution adopts a two-layer penalty-based approach with a BCD inner loop and convex surrogates for frequency-dependent absorption; a convex approximation for the absorption factor further enables tractable optimization. Numerical results show that adaptive sub-band allocation with IRS-assisted FD THz transmissions significantly improves spectral efficiency and user fairness, with notable gains over ESB and fixed-band baselines, especially as the IRS size and bandwidth grow. The proposed methods offer practical, scalable approaches to harness the wide THz spectrum in realistic propagation environments.

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.

Figures (9)

• Figure 1: An IRS-assisted multi-user FD THz communication system.
• Figure 2: Illustration of THz TWs, absorption coefficient peaks, and the allocation of sub-bands.
• Figure 3: One snapshot of constraint violation and convergence behavior of Algorithm \ref{['algorithm1']}.
• Figure 4: WMR versus the number of IRS elements.
• Figure 5: WMR versus the power budget at BS.