Enhanced BER Optimization and Jamming Resilience in Chaos Communication Systems using MIMO-OFDM and Adaptive Spreading Factors - Charitha, Manasa; Hosur, Sunil (Engineering, Technology & Applied Science Research, 2025)
The growing demand for secure communication systems necessitates addressing the limitations of conventional methods like Code Division Multiple Access (CDMA) and Frequency Hopping Spread Spectrum (FHSS) that often struggle with poor jamming resilience, suboptimal Bit Error Rate (BER) performance, and limited adaptability, especially under challenging conditions such as varying Signal-to-Noise Ratio (SNR) and Gamma-Gamma turbulence. This research proposes a chaos-based communication system integrating the Adaptive Spreading Factor Optimization Technique (ASFOT) and the Chaos-based Jamming Resilience Method (CJRM). ASFOT dynamically adjusts the spreading factor to optimize BER, achieving a 0.25% reduction compared to conventional CDMA. CJRM leverages chaotic signal properties to enhance robustness against jamming attacks, resulting in a 0.30% improvement in resilience. Furthermore, the system achieves a peak throughput of 9.5 Mbps, surpassing the 9 Mbps of conventional methods. The integration of chaos-based signals enhances spectral efficiency and communication security, making the system suitable for applications in IoT, smart cities, and military-grade networks. The conducted analysis demonstrates its superiority across performance metrics, including BER, throughput, and jamming resilience. The proposed system represents a scalable, reliable solution for modern communication challenges. Future work will focus on real-world validations, improving energy efficiency, and integrating machine learning to enable real-time adaptability and scalability for next-generation communication systems.