Rate Region of RIS-Aided URLLC Broadcast Channels: Diagonal versus Beyond Diagonal Globally Passive RIS
Mohammad Soleymani, Alessio Zappone, Eduard Jorswieck, Marco Di Renzo,, Ignacio Santamaria

TL;DR
This paper investigates the rate region of RIS-aided URLLC broadcast channels, comparing different RIS architectures, and finds that globally passive beyond diagonal RISs offer performance gains, especially under strict reliability and latency constraints.
Contribution
It introduces and analyzes the finite-block-length rate regions for three RIS architectures, highlighting the advantages of beyond diagonal globally passive RISs over diagonal and locally passive designs.
Findings
GP BD-RIS outperforms LP and GP D-RIS in enlarging feasible solutions.
Performance gains decrease as the number of RIS elements increases.
RIS deployment yields higher gains under stricter reliability and latency requirements.
Abstract
We analyze the finite-block-length rate region of wireless systems aided by reconfigurable intelligent surfaces (RISs), employing treating interference as noise. We consider three nearly passive RIS architectures, including locally passive (LP) diagonal (D), globally passive (GP) D, and GP beyond diagonal (BD) RISs. In a GP RIS, the power constraint is applied globally to the whole surface, while some elements may amplify the incident signal locally. The considered RIS architectures provide substantial performance gains compared with systems operating without RIS. GP BD-RIS outperforms, at the price of increasing the complexity, LP and GP D-RIS as it enlarges the feasible set of allowed solutions. However, the gain provided by BD-RIS decreases with the number of RIS elements. Additionally, deploying RISs provides higher gains as the reliability/latency requirement becomes more stringent.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced MIMO Systems Optimization · Advanced Wireless Communication Techniques · Error Correcting Code Techniques
MethodsSparse Evolutionary Training
