DISH WIRELESS L.L.C. (20240334463). ADAPTIVE DISTRIBUTED UNIT (DU) SCHEDULER simplified abstract
Contents
ADAPTIVE DISTRIBUTED UNIT (DU) SCHEDULER
Organization Name
Inventor(s)
Sourabh Gupta of Ashburn VA (US)
Gurpreet Sohi of Parker CO (US)
ADAPTIVE DISTRIBUTED UNIT (DU) SCHEDULER - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240334463 titled 'ADAPTIVE DISTRIBUTED UNIT (DU) SCHEDULER
Simplified Explanation: The patent application describes an adaptive DU scheduler that enhances user experiences on higher channel bandwidths in a wireless telecommunication network, such as a 5G network, without dropping high priority traffic like voice over new radio (VoNR).
Key Features and Innovation:
- Central scheduler for maximizing overall throughput based on received parameter values
- Intelligence layer with AI/ML models to improve performance for all cells
- AI/ML models for each site type based on traffic distribution
- Centralized RAN pooling
- Containerized DU server with master controller pod
- DU common scheduler managing all cells
Potential Applications: This technology can be applied in wireless telecommunication networks, particularly in 5G networks, to optimize throughput and prioritize high priority traffic like VoNR.
Problems Solved: This technology addresses the challenge of increasing user experiences on higher channel bandwidths while ensuring no drops for high priority traffic in wireless networks.
Benefits:
- Enhanced user experiences on higher channel bandwidths
- Prioritization of high priority traffic like VoNR
- Optimization of overall throughput in the network
Commercial Applications: Potential commercial applications include improving network performance, enhancing user experiences, and ensuring seamless connectivity for high priority traffic in wireless telecommunication networks.
Prior Art: Readers can explore prior art related to adaptive DU schedulers, AI/ML models in wireless networks, and centralized RAN pooling to understand the evolution of similar technologies in the field.
Frequently Updated Research: Stay updated on advancements in AI/ML models for wireless networks, centralized scheduling techniques, and optimization strategies for 5G networks to further enhance the performance of adaptive DU schedulers.
Questions about Adaptive DU Scheduler: 1. How does the adaptive DU scheduler prioritize high priority traffic like VoNR? 2. What are the key benefits of using AI/ML models in the intelligence layer of the scheduler?
Original Abstract Submitted
embodiments are directed towards an adaptive du scheduler that increases the user experiences on higher channel bandwidths (bws) while ensuring no drops for voice over new radio (vonr) or other high priority traffic. example embodiments include systems and methods for an adaptive distributed unit (du) scheduler in a wireless telecommunication network, such as a wireless 5g network. example embodiments include systems and methods that include: a central scheduler for maximizing overall throughput based on received parameter values; maximizing the overall cell site throughput; an intelligence layer that has an artificial intelligence and/or machine learning (ai/ml) model that increases the performance for all the cells by sending info to central scheduler for each of the cells; an intelligence layer that has an ai/ml models for each site type based on the traffic distribution across each cell; centralized ran pooling; a containerized du server with master a controller pod controlling individual cell pods; and a containerized du server with a du common scheduler managing all the cells.
