Joint Optimization Algorithm for Multi-Dimensional Wireless Communication Resources Adapt to Deterministic Monitoring of Power Distribution Areas

With a growing penetration of distributed renewable energy, it is becoming increasingly evident that the monitoring service of power distribution area is characterized by multiple concurrency and time delay sensitivity. Correspondingly, massive amounts of differentiated data need to be collected, which dramatically increases the demand for technologies like ultra-reliable low-latency communication (URLLC) and enhanced mobile bandwidth (eMBB). However, due to limited wireless communication resource in power distribution areas, the major difficulty of improving monitoring certainty under the delay perspective lies in efficient and reasonable joint allocation of the multi-dimensional resources. To this end, a joint optimization algorithm for multi-dimensional wireless communication resources adapt to deterministic monitoring of power distribution areas is proposed. Firstly, the joint optimization problem for spectrum resource blocks (RBs) and power scheduling is constructed, and then it is decoupled in layers consisted of eMBB-RB scheduling layer, URLLC-RB scheduling layer and URLLC-power allocation layer and solved by the greedy strategy, improved plant growth simulation algorithm and rigorous theory analysis combined with block coordinate descent. The simulation results validate that the proposed algorithm swiftly and rationally allocates multi-dimensional wireless communication resources to massive and concurrent services, which satisfies the diverse QoS demands and improves the monitoring certainty of the power distribution areas.