# Towards Sustainability in 6G and beyond: Challenges and Opportunities of Open RAN

arXiv: https://arxiv.org/abs/2503.08353 · HTML: https://mlsanity.com/paper/2503.08353/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Mar 2025.

## Built on by (most cited first, 5 of 5)

- [Adaptive End-to-End Transceiver Design for NextG Pilot-Free and CP-Free Wireless Systems](https://mlsanity.com/paper/2510.25416/) (2025)
- [Towards 6G Native-AI Edge Networks: A Semantic-Aware and Agentic Intelligence Paradigm](https://mlsanity.com/paper/2512.04405/) (2025)
- [An Explainable AI Framework for Dynamic Resource Management in Vehicular Network Slicing](https://mlsanity.com/paper/2506.11882/) (2025)
- [Energy-Aware 6G Network Design: A Survey](https://mlsanity.com/paper/2509.11289/) (2025)
- [Adaptive Machine Learning Framework for UAV Trajectory Optimization in O-RAN](https://mlsanity.com/paper/2606.24483/) (2026)

## Abstract (arXiv)

The transition to 6G is expected to bring significant advancements, including much higher data rates, enhanced reliability and ultra-low latency compared to previous generations. Although 6G is anticipated to be 100 times more energy efficient, this increased efficiency does not necessarily mean reduced energy consumption or enhanced sustainability. Network sustainability encompasses a broader scope, integrating business viability, environmental sustainability, and social responsibility. This paper explores the sustainability requirements for 6G and proposes Open RAN as a key architectural solution. By enabling network diversification, fostering open and continuous innovation, and integrating AI/ML, Open RAN can promote sustainability in 6G. The paper identifies high energy consumption and e-waste generation as critical sustainability challenges and discusses how Open RAN can address these issues through softwarisation, edge computing, and AI integration.