# Exploring the 6G Potentials: Immersive, Hyper Reliable, and Low-Latency Communication

arXiv: https://arxiv.org/abs/2407.11051 · HTML: https://mlsanity.com/paper/2407.11051/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jul 2024.

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

- [AI and Semantic Communication for Infrastructure Monitoring in 6G-Driven Drone Swarms](https://mlsanity.com/paper/2503.00053/) (2025)
- [QoE-Aware Service Provision for Mobile AR Rendering: An Agent-Driven Approach](https://mlsanity.com/paper/2508.08627/) (2025)
- [SABER: Symbolic Regression-based Angle of Arrival and Beam Pattern Estimator](https://mlsanity.com/paper/2510.26340/) (2025)
- [Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions](https://mlsanity.com/paper/2604.25018/) (2026)
- [WALoMA: A Multitask Wireless Foundation Model via Adaptive Low-Rank Masked Autoencoders](https://mlsanity.com/paper/2607.25763/) (2026)

## Abstract (arXiv)

The transition towards the sixth-generation (6G) wireless telecommunications networks introduces significant challenges for researchers and industry stakeholders. The 6G technology aims to enhance existing usage scenarios through supporting innovative applications that require stringent key performance indicators (KPIs). In some critical use cases of 6G, multiple KPIs, including immersive throughput, with an envisioned peak data rate of 1 Tbps, hyper-reliability, in the range of 10-5 to 10-7, and hyper low-latency, between 0.1 and 1 ms, must be achieved simultaneously to deliver the expected service experience. However, this is challenging due to the conflicting nature of these KPIs. This article proposes a new service class of 6G as immersive, hyper reliable, and low-latency communication (IHRLLC), and introduces a potential network architecture to achieve the associated KPIs. Specifically, enhanced technologies, such as ultra-massive multiple-input multiple-output (umMIMO)-aided terahertz (THz) communications, reconfigurable intelligent surfaces (RIS), and non-terrestrial networks (NTN), are viewed as the key enablers for achieving immersive data rates and hyper reliability. Given the computational complexity involved in employing these technologies, we propose mathematical and computational enabling technologies, such as learn-to-optimize (L2O), generative-AI (GenAI), quantum computing, and network digital twin (NDT), to complement the proposed architecture and optimize the latency.