Theoretical Analysis of REM-Based Handover Algorithm for Heterogeneous Networks

Abstract

Handover has been a widely studied topic since the beginning of the mobile communications era, but with the advent of another generation, it is worth seeing it with fresh eyes. Data traffic is expected to keep growing as new use cases will coexist under the same umbrella, e.g., vehicle-to-vehicle or massive-machine-type communications. Heterogeneous networks will give way to multi-tiered networks, and mobility management will become challenging once again. Under the current approach, based uniquely on measurements, the number of handovers will soar, so will the signaling. We propose a handover algorithm that employs multidimensional radio-cognitive databases, namely radio environment maps, to predict the best network connection according to the user's trajectory. Radio environment maps have been extensively used in spectrum-sharing scenarios, and recently, some advances in other areas have been supported by them, such as coverage deployment or interference management. We also present a geometric model that translates the 3GPP specifications into geometry and introduce a new framework that can give useful insights into our proposed technique's performance. We validate our framework through Monte Carlo simulations, and the results show that a drastic reduction of at least 10% in the ping-pong handovers can be achieved, thus reducing the signaling needed.INDEX TERMS Handover, handover failure, heterogeneous networks, ping-pong handover, radio environment map.

Feasibility of Location-Aware Handover for Autonomous Vehicles in Industrial Multi-Radio Environments

“…Via continuous interaction with the environment, an optimized handoff strategy is achieved, i.e., the QoE is maximized based on created mappings between QoS metrics and achieved subjective experience on the side of UEs). Meanwhile, in [17], the REM as well as the UE trajectories are considered to predict the quality of network connectivity that is then exploited for handover process. It is seen that the handover performance improves when the time-to-trigger, the UE velocity, and the location error are low.…”

“…In the context of multi-RATs and SCNs, seamlessly handing over to or selecting a network/RAT, which provides the best possible QoS to the UE, remains a crucial enabler of a self-organized communication system, in which the connected vehicles/robots are capable of performing efficient handover in a self-organized manner via the obtained location awareness, such that the throughput as well as the link quality are jointly optimized. Apart from the IEEE 802.21 multimedia-independent handover (MIH) standard that supports a QoS-based handover within the HetNets, several works [6][7][8][9][10][11][12][13][14][15][16][17][18] investigated the location-aware handover (LHO) and/or location-aware network selection (LNS) strategy ensuring that the mobile users have access to the required media service via the best available network. The objective of our work is therefore to investigate the feasibility and benefits of such efficient handover decision making schemes (i.e., the LHO) when integrating the positioning solutions.…”

Handover Management of Drones in Future Mobile Networks: 6G Technologies

“…In [11], the network's hierarchical structure and location information are utilized to perform faster handoffs. The authors of [12] focused on an algorithm for predicting the best network to perform HO based on the user's trajectory in heterogeneous networks. Another study on Heterogeneous Networks (HetNets) is presented in [13].…”

Beyond 5G: Big Data Processing for Better Spectrum Utilization

“…On top of that, they contain various types of network-and service-related data, such as traffic maps (distribution of requested or served traffic, traffic patterns), or trajectory databases (mobility patterns of users) [9]. In [10] the authors considered the usage of REM, a kind of RSM, for reducing the number of handovers by predicting the trajectory of the users. Knowing the channel characteristics (stored in REM) and the prospective route of the user, the system procedure of the hand-off may not be initiated if the so-called ping-pong effect is expected.…”

“…However, the more data is required by the DSM operation, the higher the operational costs and the load on the backhaul part of a system. For this reason, current technologies restrict the RSM to statistical databases which are proven suitable mainly for long-term system optimization [9]- [10]. Particularly, in [11] the authors discussed the ways how in general the artificial-intelligenceoriented algorithms could improve 5G radio access networks.…”