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Published on: February 6, 2014
Performance analysis over q-Weibull fading channels for symbol error probability evaluation using a tighter Gaussian
Sarbeswar Samal1, Sujata Chakravarty1, Tanmay Mukherjee2
1Department of Computer Science and Engineering, Centurion University of Technology and Management, Jatni, Bhubaneswar, Odisha, 752050, India.
This study introduces a novel approximation for the Gaussian Q-function to accurately calculate symbol error probability (SEP) in wireless systems. The new method offers a tighter fit across all signal-to-noise ratios (SNR) and provides analytical solutions for the q-Weibull fading channel.
Area of Science:
- Wireless Communications
- Information Theory
- Mathematical Analysis
Background:
- Accurate evaluation of symbol error probability (SEP) is crucial for wireless system performance.
- Existing approximations for the Gaussian Q-function may lack accuracy across the full signal-to-noise ratio (SNR) range.
- The q-Weibull fading model, based on Tsallis' entropy, offers adaptive characteristics for modeling wireless channels.
Purpose of the Study:
- To develop a tight and closed-form approximation for the Gaussian Q-function.
- To derive an analytical solution for SEP over the q-Weibull fading channel.
- To analyze performance metrics like Level Crossing Rate (LCR) and Average Fade Duration (AFD) over the q-Weibull model.
Main Methods:
- Employing the Gauss-Legendre four-point rule to derive an exponential-type approximation for the Gaussian Q-function.
- Applying the derived approximation to obtain analytical SEP solutions for the q-Weibull fading channel.
- Investigating the impact of the entropic index (q) and shape parameter (λ) on SEP, LCR, and AFD.
Main Results:
- The proposed exponential-type approximation demonstrates superior agreement compared to existing methods for SEP computation.
- The approximation provides a tighter fit across low-to-high SNR ranges.
- Analytical solutions for SEP, LCR, and AFD over the q-Weibull channel were successfully obtained, showing adaptive behavior with varying 'q'.
Conclusions:
- The novel Gaussian Q-function approximation enhances SEP calculation accuracy in wireless fading environments.
- The analytical solutions for the q-Weibull channel provide valuable insights into system performance under adaptive fading conditions.
- This research offers a more accurate and flexible approach to modeling and analyzing wireless communication systems.
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