Trade-off analysis between delay and throughput of RAN slicing for smart grid

Emerging power services with massive connections and real-time control have different requirements on delay, rate, reliability, etc. In order to meet the diversified requirements of power services, network slicing can provide guarantee for the wide application of 5G in power. The current research on network slicing adapting power services is still in its infancy. This paper proposes a trade-off analysis method for radio access network (RAN) slice delay and throughput based on dynamic intelligent resource allocation to meet the different QoS requirements of different services in smart grid scenarios. Firstly, clustering analysis is used to classify the communication requirements of smart grid services. A throughput demand model for enhanced mobile broadband (eMBB) slice users based on importance and a delay constraint model for ultra-reliable and low latency communication (uRLLC) slice users are constructed, and a throughput model for slice users based on cell capacity limitation is constructed. Then, the problem model of maximizing the throughput of the eMBB slice by reasonably allocating resource blocks and power under the premise of ensuring the delay of the uRLLC slice is established. The Lyapunov drift plus penalty function method is used to convert the above problem into a tractable form, and then the problem is solved by the active set method. Simulation results show that the different QoS requirements of smart grid services will significantly affect the actual queue length of the uRLLC slice as well as the throughput of the eMBB slice.

Automated summary

This paper introduces a research method on power service network slicing based on dynamic intelligent resource allocation to meet different QoS requirements. By modeling the throughput and latency of eMBB and uRLLC slice users, a mathematical model for maximizing eMBB slice throughput while ensuring uRLLC slice latency is established.