5646

5G-and-beyond cellular network systems are increasingly being explored for ultra-reliable, low-latency communications in important domains such as industrial automation.  These applications demand a high level of predictability in per-packet communication reliability to ensure that data reaches their destination within strict timing constraints.

 

In this invention, we propose a transformative approach to joint wireless transmission scheduling and power control, denoted by PktR. PktR ensures application-specific per-packet communication reliability as well as high channel spatial reuse and high network throughput, and it is designed as a closed-loop system, incorporating novel mechanisms for the Gain-Ratio-K (GRK) interference modeling, mean-field game-theoretic optimization, and transmit power control. This design ensures predictable interference control for receivers as well as agile, fine-grained transmit power control at transmitters. 
This technology implemented PktR using the open-source 5G platform srsRAN, and we have validated the design and implementation of PktR through extensive measurement studies using real-world hardware and the Colosseum wireless network emulator.

• PktR ensures application-specific per-packet communication reliability as well as high channel spatial reuse and high network throughput, and it is designed as a closed-loop system, incorporating novel mechanisms for the Gain-Ratio-K (GRK) interference modeling, mean-field game-theoretic optimization, and transmit power control

• High per-packet communication SINR (e.g., 20dB) which leads towards high, per-packet communication reliability success probability

• Predictable interference control for receivers in a large, distributed network

• Highly-agile fine-tuning of transmit power at the transmitters of such a large, distributed network

• High success probability (e.g., 0.9) across diverse network and environmental settings

Autonomous vehicles, Industrial automation, healthcare, augmented/virtual reality, smart grids

• “Analysis of Joint Scheduling and Power Control for Predictable URLLC in Industrial Wireless Networks”, Zhang et al., NSF Public Access Repository (NSF-PAR) – Journal Name - IEEE International Conference on Industrial Internet (ICII), Date Published:  January 1, 2019 Analysis of Joint Scheduling and Power Control for Predictable URLLC in Industrial Wireless Networks (Conference Paper) | NSF PAGES

• “Analysis of Joint Scheduling and Power Control for Predictable URLLC in Industrial Wireless Networks”, Zhang et al., IEEE, Date added to IEEE Xplore:  19 May 2020;  Date of Conference:  11-12 November 2019.  Analysis of Joint Scheduling and Power Control for Predictable URLLC in Industrial Wireless Networks | IEEE Conference Publication | IEEE Xplore

Patent(s) applied for