A Chaos Based Proactive Security Approach Through PAPR Reduction in Web 3.0 and IoT Networks

It can be concluded from the previous discussions that PAPR reduction plays a strategic role in enabling the wireless foundation of Web 3.0. By improving power efficiency, securing physical-layer communication, supporting decentralized edge nodes, and enhancing QoS for immersive applications, PAPR reduction connects the physical wireless infrastructure with the decentralized philosophies of Web 3.0. As future networks transition into 6G with native blockchain integration, metaverse services, and distributed AI, PAPR-optimized waveforms will remain fundamental to achieving reliability, sustainability, communication in next-generation digital ecosystems.. A modification to the selective mapping technique has been proposed so as to reduce the PAPR of the system. The CCDF has been used for the analysis of the PAPR of the system. It can be seen from the results that the proposed system attains extremely low values of PAPR in comparison to previous baseline approaches thereby increasing system security.

1.      L. Jain and N. Joshi, "Impacts of Web 3.0 on Cyber Security: Challenges and Countermeasures," 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit), Greater Noida, India, 2024, pp. 912-917. 2.      J Zhu, F Li, J Chen, “A survey of blockchain, artificial intelligence, and edge computing for Web 3.0”, Computer Science Review, Elsevier, 2024, vol.54, 100667. 3.      F. S. Shawqi, L. Audah, A. T. Hammoodi, M. M. Hamdi and A. H. Mohammed, "A Review of PAPR Reduction Techniques for UFMC Waveform," 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2020, pp. 1-6 4.      S. Gökceli et al., "Novel Iterative Clipping and Error Filtering Methods for Efficient PAPR Reduction in 5G and Beyond," in IEEE Open Journal of the Communications Society, 2021, vol. 2, pp. 48-66. 5.      B. Tang, K. Qin and H. Mei, "A Hybrid Approach to Reduce the PAPR of OFDM Signals Using Clipping and Companding," in IEEE Access, 2020, vol. 8, pp. 18984-18994. 6.      R Niwareeba, MA Cox, L Cheng, “Low complexity hybrid SLM for PAPR mitigation for ACO OFDM”, ICT Express, Elsevier 2022, vol.8, no.1, pp.72-76. 7.      W. Ma, C. Qi and G. Y. Li, "High-Resolution Channel Estimation for Frequency-Selective mmWave Massive MIMO Systems," in IEEE Transactions on Wireless Communications, vol. 19, no. 5, pp. 3517-3529, May 2020 8.        K. Venugopal, N. González-Prelcic and R. W. Heath, "Optimality of Frequency Flat Precoding in Frequency Selective Millimeter Wave Channels," in IEEE Wireless Communications Letters, vol. 6, no. 3, pp. 330-333, June 2017. 9.      P. Singh, E. Sharma, K. Vasudevan and R. Budhiraja, "CFO and Channel Estimation for Frequency Selective MIMO-FBMC/OQAM Systems," in IEEE Wireless Communications Letters, vol. 7, no. 5, pp. 844-847, Oct. 2018. 10.   R. Zayani, J. -B. Doré, B. Miscopein and D. Demmer, "Local PAPR-Aware Precoding for Energy-Efficient Cell-Free Massive MIMO-OFDM Systems," in IEEE Transactions on Green Communications and Networking, 2023, vol. 7, no. 3, pp. 1267-1284.