  The ever-increasing demand for data services and the proliferation of user
equipment (UE) have resulted in a significant rise in the volume of mobile
traffic. Moreover, in multi-band networks, non-uniform traffic distribution
among different operational bands can lead to congestion, which can adversely
impact the user's quality of experience. Load balancing is a critical aspect of
network optimization, where it ensures that the traffic is evenly distributed
among different bands, avoiding congestion and ensuring better user experience.
Traditional load balancing approaches rely only on the band channel quality as
a load indicator and to move UEs between bands, which disregards the UE's
demands and the band resource, and hence, leading to a suboptimal balancing and
utilization of resources. To address this challenge, we propose an event-based
algorithm, in which we model the load balancing problem as a multi-objective
stochastic optimization, and assign UEs to bands in a probabilistic manner. The
goal is to evenly distribute traffic across available bands according to their
resources, while maintaining minimal number of inter-frequency handovers to
avoid the signaling overhead and the interruption time. Simulation results show
that the proposed algorithm enhances the network's performance and outperforms
traditional load balancing approaches in terms of throughput and interruption
time.
