Computational Efficient ER of Wireless Nano Sensor Network under Interference
Paneri Fulbandhe, Sharayu Kalambe, Gunjal Chauhan, Nitin Rakesh, Monali Gulhane, Sandeep Kumar · 2024
The Wireless Nano Sensor Network (WNSN) area is the most important paradigm used in monitoring physical or environmental conditions. However, computational efficiency is the most challenging issue of WNSN. Therefore, this research presents an MGF based computationally efficient approach for WNSN. In particular, this paper presents a novel analytical expression of the Error Rate (ER) of WNSN under interference using MGF based approach. Finally, the impact of different boundaries such as spatial density of nanosensors nodes (λ), SIR of interferers (γI), SNR of interferers (γ), and path loss exponent (v) are investigated. The results show that for increasing values of SNR, the ER decreases. Whereas, for increasing values of either spatial density of nanosensor nodes or SIR, the ER increases. Moreover, reproduced discoveries show ideal concurrence with the hypothetical foundations. MAPLE 18, which is a computational numerical programming bundle, is utilized in the examination.