AI BASED ORTHOGONAL MULTIPLE ACCESS 6G NETWORK WITH HIGH SPEED
Keywords:
6G Networks, Artificial Intelligence, Orthogonal Multiple Access, Machine Learning, Deep Neural Networks, Beamforming, Resource Allocation, Spectral Efficiency, Ultra-Low Latency, Massive Connectivity.Abstract
The evolution towards sixth-generation (6G) wireless networks demands revolutionary approaches to address
unprecedented data rates, ultra-low latency, and massive connectivity requirements. This research investigates the
integration of artificial intelligence (AI) with orthogonal multiple access (OMA) techniques to enhance 6G network
performance and achieve significantly higher data transmission speeds. The study explores machine learning algorithms,
deep neural networks, and reinforcement learning methods to optimize resource allocation, interference mitigation, and
spectral efficiency in 6G-OMA systems. Through comprehensive analysis of primary and secondary data, this research
demonstrates that AI-enhanced OMA schemes can achieve data rates exceeding 1 Tbps with latency reduction of up to
85% compared to conventional 5G networks. The findings reveal that intelligent beamforming, predictive resource
management, and adaptive modulation techniques significantly improve network capacity and energy efficiency.
Experimental results indicate that AI-driven OMA systems can support up to 10^7 connected devices per square kilometer
while maintaining quality of service standards. This research contributes to the theoretical foundation and practical
implementation strategies for next-generation wireless communication systems, providing insights for network operators,
equipment manufacturers, and standardization bodies working towards 6G deployment.