Robust Beamforming Design for Energy Efficiency and Spectral Efficiency Tradeoff in Multi-STAR-RIS-Aided C-HRSMA.

Area of Science:

• Wireless Communication
• Signal Processing
• Optimization Theory

Background:

• Cognitive hierarchical rate-splitting multiple access (C-HRSMA) systems face performance limitations due to interference, especially under imperfect channel state information (ICSI).
• Reconfigurable intelligent surfaces (RIS) offer a promising solution for wireless environment manipulation, but their integration with advanced multiple access schemes requires careful design.

Purpose of the Study:

• To investigate the performance enhancement of a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted cognitive hierarchical rate-splitting multiple access (C-HRSMA) system.
• To address the challenges posed by imperfect channel state information (ICSI) and optimize system performance.

Main Methods:

• Formulation of a non-convex optimization problem involving STAR-RIS phase-shift matrix, base station beamforming vector, and common rate allocation vector.
• Application of an alternating optimization (AO) technique to decouple the problem.
• Utilization of S-procedure and successive convex approximation (SCA) to solve subproblems.

Main Results:

• Effective mitigation of inter-group common stream interference within C-HRSMA by exploiting STAR-RIS capabilities.
• Achievement of higher spectral efficiency (SE) through optimized resource allocation.
• Demonstrated superior SE and energy efficiency (EE) performance compared to benchmark algorithms.

Conclusions:

• The proposed STAR-RIS-assisted C-HRSMA system effectively enhances spectral and energy efficiency under ICSI.
• The developed alternating optimization approach provides a viable solution for complex non-convex optimization problems in advanced wireless systems.
• This work offers a significant advancement in intelligent reflecting surface-aided wireless network design.