[Paper Review] Energy Efficiency Maximization of Simultaneous Transmission and Reflection RIS Assisted Full-Duplex Communications

Pengxin Guan, Yiru Wang+2 more|arXiv (Cornell University)|Mar 14, 2022

Advanced Wireless Communication Technologies4 citations

TL;DR

This paper proposes an energy efficiency (EE) maximization framework for a simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS)-assisted full-duplex (FD) communication system. By jointly optimizing base station and uplink user transmit power and STAR-RIS passive beamforming via alternating optimization, Dinkelbach’s method, and successive convex approximation, the scheme achieves superior EE performance compared to benchmarks, especially under high RIS element counts and effective self-interference cancellation.

ABSTRACT

This work studies the effectiveness of a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) aided Full-Duplex (FD) communication system. We aim to maximize the energy efficiency by jointly optimizing the transmit power and passive beamforming at the STAR-RIS. We propose an efficient algorithm to optimize them iteratively under the alternating optimization framework. The successive convex approximation (SCA) and Dinkelbach's method are used to solve the power optimization subproblem. The penalty-based method is used to design passive beamforming at the STAR-RIS. Numerical results verify the convergence and effectiveness of the proposed algorithm, and further reveal the benifits of the combining of the STAR-RIS and FD communication compared to benchmarks.

Motivation & Objective

• Address the lack of research on energy efficiency in STAR-RIS-aided full-duplex systems.
• Overcome the non-convexity of the joint power and beamforming optimization problem in FD communication with STAR-RIS.
• Maximize system energy efficiency while satisfying minimum rate constraints for uplink and downlink users.
• Design a low-complexity, convergent algorithm combining Dinkelbach’s method and successive convex approximation for practical deployment.
• Demonstrate the superiority of combining STAR-RIS and FD technologies in enhancing spectral and energy efficiency.

Proposed method

• Decompose the non-convex EE maximization problem into two subproblems: transmit power optimization and passive beamforming design.
• Apply the alternating optimization (AO) framework to iteratively solve the two subproblems.
• Use Dinkelbach’s method to solve the power optimization subproblem by transforming the fractional programming into a sequence of parametric subproblems.
• Employ a penalty-based method combined with successive convex approximation (SCA) to handle the non-convex beamforming constraints and converge to a stationary point.
• Enforce energy conservation at each STAR-RIS element via the constraint βₘᵗ + βₘʳ = 1 for all m.
• Ensure convergence by leveraging the monotonic increase of EE through iterative optimization and bounded system resources.

Experimental results

Research questions

• RQ1 How does the integration of STAR-RIS and full-duplex communication enhance system energy efficiency compared to conventional half-duplex or RIS-only systems?
• RQ2 What is the optimal joint design of transmit power and passive beamforming for maximizing EE in a STAR-RIS-aided FD system?
• RQ3 How do residual self-interference and circuit power at STAR-RIS elements impact the achievable energy efficiency?
• RQ4 To what extent does increasing the number of RIS elements improve system EE under the proposed optimization framework?
• RQ5 How does the proposed algorithm compare in performance and convergence to baseline schemes such as HD, conventional RIS, and sum-rate maximization?

Key findings

• The proposed STAR-RIS-aided FD system with EE maximization (SR-FD-EEM) achieves the highest energy efficiency across all tested scenarios, outperforming HD and conventional RIS-based FD schemes.
• Energy efficiency increases with the number of STAR-RIS elements due to improved spectral efficiency with marginal power increase, with SR-FD-EEM showing the steepest growth.
• Residual self-interference degrades EE in FD systems, but the proposed scheme maintains high EE due to effective self-interference cancellation, unlike HD schemes which are unaffected by SI.
• The EE of the sum-rate maximization scheme (SR-FD-SRM) initially increases with uplink power but eventually declines due to excessive energy consumption, while EE-maximization schemes show a monotonic rise to an optimal point.
• Higher circuit power per STAR-RIS element (Pₛ) reduces system EE, but SR-FD-EEM maintains a significant performance gain over benchmarks even at high Pₛ values.
• The proposed AO-based algorithm converges reliably, with computational complexity on the order of O(L(2Lₚ + 2LₒLᵢM³·⁵)), ensuring practical feasibility for large-scale deployments.