Reconfigurable Intelligent Surface-Assisted Multi-User Secrecy Transmission With Low-Resolution DACs

• Published in: IEEE transactions on green communications and networking 2024-09, Vol.8 (3), p.1205-1221
• Main Authors: Li, Kexin, Du, Huiqin, Li, Si
• Format: Article
• Language: English
• Subjects: Algorithms; Array signal processing; Backhaul networks; Beamforming; Closed form solutions; Communication system security; Constraints; DC-AC power converters; Digital to analog converters; digital-to-analog converters (DACs); Logarithms; Mathematical programming; Mixed integer; Optimization; Phase shift; Programming; Quadratic programming; quadratically constrained quadratic programming; Quantization (signal); Reconfigurable intelligent surface (RIS); Reconfigurable intelligent surfaces; Relaxation method (mathematics); Scheduling; Sums
• ISSN: 2473-2400; 2473-2400
• DOI: 10.1109/TGCN.2024.3362866

This paper considers a reconfigurable intelligent surface (RIS)-assisted multi-user secrecy transmission in the presence of low-resolution digital-to-analog converters (DACs) at a small-cell base station (SBS). The weighted sum secrecy rate (WSSR) is maximized by jointly designing the active beamforming and RIS reflecting phase shift subject to the transmit power and the phase unit-modulus constraints. However, the problem involves two sum-of-logarithms and highly coupled optimization variables. To tackle the non-convex fractional programming problem with multiple ratios, we employ a lower linearization approach for logarithm subtraction and decompose the problem into two quadratically constrained quadratic programming subproblems. The optimum active beamforming is determined using a semi-definite relaxation method, and the a closed-form solution of RIS phase shift matrix is derived through the alternating direction method of multiplier. Moreover, considering practical finite-capacity backhaul link, we develop the user scheduling strategy using the power of transmit beamforming as a discrete indicator and formulate the user scheduling as a mixed-integer constraint. The joint optimization of user scheduling and WSSR is investigated by maximizing the network utility with a \ell _{1} -norm constraint. Simulation results demonstrate the effectiveness of the proposed algorithm in achieving significant WSSR performance even in the presence of low-resolution DACs. Furthermore, these results show that the joint optimization of WSSR and user scheduling can maximize the network utility by selecting the activated subset of served users.