Statistics of the Sum of Double Random Variables and Their Applications in Performance Analysis and Optimization of Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface-Assisted Non-Orthogonal Multi-Access Systems
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View abstract on PubMed
Summary
This summary is machine-generated.This study enhances 6G wireless networks using simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). The research improves outage probability and data rates in energy-harvesting networks, outperforming traditional systems.
Area Of Science
- Wireless Communication
- Signal Processing
- Information Theory
Background
- Sixth-generation (6G) wireless communication demands advanced solutions for low power and seamless coverage.
- Reconfigurable intelligent surfaces (RIS) offer a promising approach, with STAR-RIS enabling simultaneous transmission and reflection.
- Performance analysis of RIS-assisted networks requires understanding the statistics of double random variables.
Purpose Of The Study
- To analyze the performance of a STAR-RIS network integrated with power beacon (PB) energy-harvesting (EH) and NOMA.
- To investigate the impact of imperfect successive interference cancellation (ipSIC) on system metrics.
- To derive closed-form expressions for outage probability (OP) and ergodic rate.
Main Methods
- Application of sum of double random variables statistics for performance analysis.
- Development of analytical models for both imperfect and perfect successive interference cancellation (pSIC) scenarios.
- Extensive simulations to validate analytical results and optimize system parameters.
Main Results
- Closed-form expressions for OP and ergodic rate derived for both ipSIC and pSIC.
- Identification of optimal system parameters (time-switching factor, reflecting elements, power allocation) to minimize OP.
- Demonstration of the proposed STAR-RIS framework's superiority over conventional NOMA and OMA systems.
Conclusions
- The proposed STAR-RIS framework significantly enhances performance in 6G wireless networks.
- The statistical analysis provides valuable insights for designing efficient energy-harvesting NOMA systems.
- Optimized parameter selection is crucial for maximizing system efficiency and minimizing outage probability.
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