A Genetic Algorithm Based Scheduling Method With Carrier Aggregation In 5G Networks

Abstract

Abstract Recently, 5G has become an important mechanism to serve a growing amount of users in the network, which provides enhanced mobile broadband (eMBB) and ultra-reliable low latency communications (URLLC) services. Meanwhile, Carrier Aggregation (CA) is a promising 5G technology which lets users aggregate fragmented carrier components (CCs) to enhance transmission efficiency. This paper addresses 5G scheduling problem in the CA-enabled eMBB–URLLC coexistence network using genetic algorithm (GA). The key idea is first treating the serving time slot of each user equipment (UE) as a gene and combining all genes to form a chromosome, then generating a set of chromosomes as the initial population and letting the population evolve to iteratively select the fittest one as the resource scheduling decision. Up to now, this is the first work using GA for solving the scheduling problem in the CA-enabled 5G network. Simulation results show that our proposed method can serve the most UEs ($4\%$) with the highest throughput ($7.1\%$) and lower delay.