ORTHOGONAL MULTIPLE ACCESS FOR 6G AND BEYOND USING AI

Authors

  • Anchal Kumari Research Scholar, Department of Computer Science, Radha Govind university, Ramgarh Author
  • Dr. Sanjay Kumar Professor, Department of Computer Science, Radha Govind University, Ramgarh Author

Keywords:

Orthogonal Multiple Access, Artificial Intelligence, 6G Networks, Resource Allocation, Machine Learning, Deep Learning, Spectrum Efficiency, Ultra-Reliable Low-Latency Communication, Massive MIMO, Network Optimization

Abstract

This research paper explores the integration of artificial intelligence (AI) with orthogonal multiple access (OMA)
techniques for sixth-generation (6G) wireless communication networks and beyond. As the demand for ultra-reliable,
low-latency communication continues to grow exponentially, traditional multiple access schemes face significant
challenges in spectrum efficiency, connectivity density, and energy consumption. This study investigates how AIenhanced OMA can address these challenges by optimizing resource allocation, reducing interference, and improving
overall system performance. Through comprehensive analysis of both theoretical frameworks and practical
implementations, this paper presents novel approaches to AI-driven orthogonal multiple access that can support the
massive connectivity requirements of future wireless networks. Our findings indicate that AI-enhanced OMA systems
can achieve up to 30% improvement in spectral efficiency and 25% reduction in latency compared to conventional
systems, making them crucial for meeting the demanding requirements of 6G networks and beyond.

Published

2025-04-30

Issue

Vol. 12 No. 4 (2025): April

Section

Articles