Optimized Sparrow Search-based Multiplexing of eMBB and URLLC in 5G/B5G Networks

Abstract

In 5G/B5G networks, the preemptive scheduling provides an efficient solution to the coexistence problem of eMBB/URLLC services. Current works usually assume that the downlink transmission duration of each URLLC service is within one mini-slot, which ignores the different requirements of URLLC users and may lead to the severe data rate loss of eMBB services and low resource utilization efficiency. To deal with above problem, we propose a novel URLLC preemptive strategy, where the arriving URLLC services could cross through multiple mini-slots rather than only one to puncture resources on demand. With the proposed strategy, considering the heterogeneous delay requirements of URLLC services and the preemptive influence on eMBB services, an efficient algorithm based on optimized sparrow search is also proposed. Through allocating time and frequency resources occupied by each URLLC service on de-mand, the number of URLLC services supported by the gNB is maximized while the satisfaction of eMBB services is ensured. The simulation results indicate that the proposed algorithm can achieve better performance compared with the benchmark schemes.