A Hybrid Traffic Aware Quality of Service Enhancement Technique: Integrating Ant Colony Optimization-based Cell Range Extension and Joint Transmission Coordinated Multi-point Approaches

The evolution of wireless networks into 5G and beyond envisions the deployment of Heterogeneous Networks (HetNets), characterized by the dense integration of small cells within macro cell coverage. This architectural shift introduces cell edge users, leading to heightened Inter-Cell Interference (ICI). Conventional cell association methods relying on Reference Signal Received Power (RSRP) criteria exacerbate the challenge by causing severe load imbalances. Additionally, the proliferation of ultra-dense small cells in HetNets intensifies hand-offs, contributing to a significant surge in call drop rates. These issues, along with signal interference at cell edges, collectively result in substantially declining Quality of Service (QoS). While existing studies have individually addressed these concerns, only a few studies have discussed these problems under one scenario, which is vital as they are interrelated to support the 5G and 6G networks with an enhanced QoS. Joint Transmission Coordinated Multi-point (JT-CoMP) presents a promising solution to tackle this interference challenge. On the other hand, Cell Range Extension (CRE) technique extends a cell area by virtually adding an offset or bias value to the RSRP, increasing cell-edge throughput and overall network throughput. However, utilizing a random Cell Specific Offset (CSO) value may still result in overloading the Macro Base Station (MBS). Therefore, careful selection of effective biasing values becomes crucial. Hence, this paper proposes an Ant Colony Optimization (ACO)-based CRE plus JT-CoMP technique to enhance the QoS in terms of load balancing, throughput, handover latency, and call drop rate. The proposed hybrid technique assigns each small cell the best possible bias or offset value based on the user traffic in the Base Station (BS). Simulation results show that the proposed hybrid technique outperforms state-of-the art techniques such as Channel State Information (CSI), multi-Radio Access Technology (multi-RAT), and Particle Swarm Optimization (PSO).