Mitigation of frequent-handover in 5G and beyond using handover candidate cells list optimization

Abstract

5G and beyond networks require diverse spectrum allocations: lower band for coverage, mid-band for both coverage and capacity, and higher band for high to ultra-high data rates. To meet increasing capacity demands, small cells are deployed, significantly increasing base station (BS) proximity and network densification. This results in frequent handovers; In existing techniques, the handover candidate cells list (HCL) are reported as-is to the target selection (handover decision-making) stage, which results in “unnecessary” cells included as potential handover target, leading to high unnecessary handovers, ping-pong effects, and handover failures, causing signaling overhead, network congestion, and session disruptions for mobile users. This paper proposes an optimization approach for HCL to improve handover performance in 5G and beyond networks. The approach utilizes mobility load balancing (MLB) to identify overloaded cells/BSs in the neighbor cells list (NCL), which are then excluded from the HCL prior to the target selection stage. Additionally, it considers angular displacement (proximity) to remove cells that are significantly displaced from the UE’s direction of movement. This process reduces or eliminates potentially unnecessary candidates from the handover decision phase, thereby minimizing frequent handovers, unnecessary handovers, ping-pong effects, and handover failures. A comparative analysis is presented for the handover procedure with and without HCL optimization, in both manual and auto-tuning mobility robustness optimization (MRO) methods, in absolute and relative handover measurement strategies (events). The results indicate that HCL optimization significantly enhances handover performance across various MRO methods for absolute handover measurement events while maintaining high throughput. Handover performance improvements range from 17.98% to 96.80% for the handover rate (HR)/frequency, 58.56% to 99.75% for the ping-pong handover rate (PHR), 0.62% to 84.29% for the unnecessary handover rate (UHR), and 66% to 99.90% for the handover failure rate (HFR). This analysis suggests that HCL optimization should be considered a vital component in the design and implementation of handover management and control to maximize efficiency and reliability. The proposed approach optimizes handovers with minimal additional complexity, making it a viable solution for 5G and beyond networks.