# Coverage Characterization of STAR-RIS Networks: NOMA and OMA

arXiv: https://arxiv.org/abs/2104.10006 · HTML: https://mlsanity.com/paper/2104.10006/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Apr 2021.

## Built on by (most cited first, 3 of 3)

- [Coverage and Capacity Optimization in STAR-RISs Assisted Networks: A Machine Learning Approach](https://mlsanity.com/paper/2204.06390/) (2022)
- [DRL Enabled Coverage and Capacity Optimization in STAR-RIS Assisted Networks](https://mlsanity.com/paper/2209.00511/) (2022)
- [A Particle-Swarm-Assisted Gradient Meta-Learning Algorithm for Joint Transmit Precoding and STAR-RIS Coefficient Optimization](https://mlsanity.com/paper/2609.29150/) (2026)

## Abstract (arXiv)

The novel concept of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is investigated, where incident signals can be transmitted and reflected to users located at different sides of the surface. In particular, the fundamental coverage range of STAR-RIS aided two-user communication networks is studied. A sum coverage range maximization problem is formulated for both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA), where the resource allocation at the access point and the transmission and reflection coefficients at the STAR-RIS are jointly optimized to satisfy the communication requirements of users. For NOMA, we transform the non-convex decoding order constraint into a linear constraint and the resulting problem is convex, which can be optimally solved. For OMA, we first show that the optimization problem for given time/frequency resource allocation is convex. Then, we employ the one dimensional search-based algorithm to obtain the optimal solution. Numerical results reveal that the coverage can be significantly extended by the STAR-RIS compared with conventional RISs.