Simultaneously Transmitting and Reflecting Reconfigurable Intelligent...

Paper

Abstract

Unlike conventional reflection-only reconfigurable intelligent surfaces (RISs), simultaneously transmitting and reflecting RISs (STAR-RISs) constitute a paradigm shift in intelligent surface design by facilitating electromagnetic wave manipulation in both transmission and reflection domains, thereby achieving full-space coverage and mitigating the inherent directional limitations of traditional RIS implementations. Orthogonal time frequency space (OTFS) modulation has emerged as a highly promising waveform candidate for enabling reliable and efficient communication in high-mobility environments, owing to its resilience against severe Doppler effects and time-frequency channel variations. In this paper, a new STAR-RIS aided OTFS system (STAR-RIS-OTFS), which is a promising technique for high-mobility future wireless communication systems, is proposed. The combination of these two methodologies yields enhanced bit error rate performance over conventional OTFS systems. The performance of the proposed STAR-RIS-OTFS scheme is evaluated under M-ary quadrature amplitude modulation over both Rayleigh and Nakagami-m fading channels. In addition, a detailed computational complexity analysis is carried out for the maximum likelihood detector and the enhanced low-complexity detector, considering both the proposed STAR-RIS-OTFS architecture and the benchmark system. Moreover, the effects of imperfect channel state information (CSI) on the proposed STAR-RIS-OTFS system are investigated, and comparative performance results are provided under perfect and imperfect CSI assumptions. The proposed STAR-RIS-OTFS system is evaluated through Monte Carlo simulations over high-mobility Rayleigh channels for various system parameters. It is shown that the proposed STAR-RIS-OTFS scheme outperforms the traditional OTFS technique.

Analysis

Paper intelligence

Preparing paper insights from the available abstract and paper details.

Discovery

Related papers

2026Crossref0 citations

A Review of AI Computing Hardware for Enabling 6G Wireless Networks: Neuromorphic Chips, NPUs, and TPUs

Yu-Dong Yao; Jason Lee

Jul 16, 2026AI Engineering

2026Crossref2 citations

AI‐Driven Resource Allocation and Beamforming in 6G Terahertz Networks

Altaf Hussain; Tariq Hussain

May 10, 2026International Journal of Communication Systems

2026Crossref0 citations

Radio Antennas in Sixth-Generation Mobile Wireless Systems Using Carbon Nanotubes

Jafaar Fahad A. Rida; Basim Abood

May 8, 2026Journal of Computational and Cognitive Engineering

2026Crossref0 citations

Optical integrated sensing and communication (O-ISAC): a unified framework for 6G and AI-Powered intelligent networks

Aruna Bansal; Archita Bhatnagar; Vikas Sharma; Nitin Sharma

Feb 3, 2026Journal of Optical Communications

2026PubMed

Advanced Handover Decision with Mobility Awareness for 5G/6G Mobile Networks in Ultra-Dense and Smart Cities Area.

Loutfi SI; Shayea I; Tureli U; Tashan W; Aldasheva L; Amirova A; Yedilkhan D; Amanzholova S

Jan 1, 2026Sensors (Basel, Switzerland)

2026PubMed

Distributed Antenna Array and RIS-Assisted Planning Framework for Intelligent Coverage Optimization in B5G/6G Cell-Free Massive MIMO.

Farre V; Vega-Sánchez J; Cama-Pinto A; Pacheco VG; Orozco Garzón N; Flores-Moyano R

Jan 1, 2026Sensors (Basel, Switzerland)

Source record

Publication metadata

Authors: Erdoğan Aydın
Published: Aug 21, 2026
Journal or venue: ELECTRICA
DOI: 10.5152/electrica.2026.25262
Paper type: journal article
Source: Crossref

DOI