Grant-Free Random Access for Private 5G Mobile Networks Based Internet of Energy
Minda Shi, Wei-Ping Shao, Liang Zhu, Wei Jiang, Zhi Ling · 2024
The Internet of Energy (IoE) leveraging private 5G mobile networks represents a novel approach to boosting the overall efficiency of energy infrastructure while minimizing energy waste. As the number of IoE devices grows, grant-free random access (GFRA) has garnered significant attention due to its potential to slash signaling overhead and transmission latency. In our study, we examine GFRA in cell-free massive multiple-input-multiple-output (MIMO) systems within private 5G mobile networks that accommodate mixed-type IoE devices, while also considering the implications of access delay. We introduce a method for identifying colliding devices based on signal-to-noise ratio and calculate the access success probability for each device. Furthermore, we incorporate a backoff mechanism and derive an analytical approximation for the system's average spectral efficiency. By utilizing the gradient descent optimization algorithm, we determine the optimal backoff parameters for each device type. Simulation results indicate a strong correlation among the optimal backoff parameters of diverse device types. Notably, these parameters are significantly influenced by delay constraints, yet their impact diminishes as the devices’ delay constraints approach the minimal loose boundary value.