Reconfigurable Intelligent Surfaces Enhanced Symbol Level Interference Exploitation Precoding
Reconfigurable intelligent surfaces (RIS)-aided communications are expected to provide increased degrees of freedom and enhanced performance in future wireless communications systems. This improvement is due to the ability of the RIS to optimize the propagation environment. In this letter, we investigate RIS-enhanced symbol-level interference exploitation precoding, an advanced interference management technique that can fully utilize multi-user interference to enhance the desired signals. Specifically, we formulate the precoding and RIS reflection design problem to minimize the transmit power, subject to constraints on the constructive interference (CI) and the RIS reflection coefficients. To solve this multivariable nonconvex optimization problem, we propose an efficient algorithm based on the alternating direction method of multipliers (ADMM), which allows the problem to be split into several simpler subproblems. Simulation results demonstrate that the proposed RIS-enhanced symbol-level interference exploitation precoding requires significantly lower transmit power to achieve a prescribed signal-to-interference-plus-noise ratio (SINR) threshold compared to benchmark schemes. Moreover, the proposed efficient algorithm is shown to converge within a limited number of iterations.
Authors
- A. Lee Swindlehurst (ORCID: https://orcid.org/0000-0002-0521-3107)
- Christos Masouros (ORCID: https://orcid.org/0000-0002-8259-6615)
- Xuewen Liao (ORCID: https://orcid.org/0000-0002-8273-7019)
- Junwen Yang (ORCID: https://orcid.org/0000-0002-3941-5575)
- Ang Li (ORCID: https://orcid.org/0000-0001-8235-7596)
Institutions
- University of California, Irvine (US)
- University College London (GB)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- IEEE Wireless Communications Letters
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1109/lwc.2025.3561940
- Citations
- 1
- Primary Topic
- Semiconductor Lasers and Optical Devices
- Type
- article
- Field-Weighted Citation Impact
- 0.73