Virtual Full-Duplex Communication Enabled STAR-RIS: Performance Analysis and Machine Learning-Assisted Optimization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F29142890%3A_____%2F25%3A00052437" target="_blank" >RIV/29142890:_____/25:00052437 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10835171" target="_blank" >https://ieeexplore.ieee.org/document/10835171</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TCCN.2025.3527682" target="_blank" >10.1109/TCCN.2025.3527682</a>
Alternative languages
Result language
angličtina
Original language name
Virtual Full-Duplex Communication Enabled STAR-RIS: Performance Analysis and Machine Learning-Assisted Optimization
Original language description
This work proposes a novel virtual full-duplex (VFD) communication based simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) scheme to mimic as well as outperform conventional full-duplex based STAR-RIS communication in practical high residual self-interference scenarios. For the proposed VFD based STAR-RIS (VFD-STAR-RIS) system involving multiple uplink and downlink users with user selection, analytical expressions of outage probability (OP) and ergodic rate (ER) are presented for downlink and uplink users. Thereafter, to minimize STAR-RIS aided inter-user interferences, we study joint optimization of user power allocations, reflection amplitude, transmission amplitude and element partitioning (JPRTE) for system OP (SOP) minimization and ergodic sum rate (ESR) maximization. A particle swarm optimization (PSO) based solution is used to solve the JPRTE problem of minimizing the SOP (JPRTE-SOP). However, due to the complexity involved in the ER expressions, applying PSO directly to the JPRTE problem of ESR maximization (JPRTE-ESR) will require significant convergence time. Thus, a machine learning (ML) based solution is proposed where the ER expressions are first closely approximated via a ML architecture, and thereafter PSO is applied to obtain a solution having a very low computational time. Monte-Carlo simulations are carried out to demonstrate efficacy of proposed VFD-STAR-RIS scheme, JPRTE-SOP, and JPRTE-ESR solutions to draw out useful inferences.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Cognitive Communications and Networking
ISSN
2332-7731
e-ISSN
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Volume of the periodical
11
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
3260-3275
UT code for WoS article
001589934200006
EID of the result in the Scopus database
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