Abstract
The emerging 5G mobile network technology is envisioned to provide an efficient platform to interconnect machines, objects, and devices in addition to interconnecting people. Equipped with peak data rates, low latency, and massive capacity, 5G technology will empower new user experiences such as virtual reality and augmented reality and provide new service areas such as connecting massive IoT. Dual connectivity is an important feature where 5G systems are overlaid on the existing 4G core network. In this paper, we propose an MM (mobility management) algorithm to efficiently perform handovers between 4G and 5G RATs (radio access technologies). Our proposed MM algorithm utilizes the strength of DC (dual connectivity) for MM as DC inherently has lesser amount of handover interruption as compared to conventional hard handover. Our MM scheme suggests appropriate data split mechanism between 4G and 5G RATs based on application-specific strategy. We provide a framework based on probabilistic model checking that leverages DC and suggests strategy-based data split mechanism for a mobile user for a variety of market verticals. We model the system as MDP (Markov decision process) where a controller breaks all the nondeterminism in the MDP based on reward calculations. The proposed framework is implemented in a well known model checker and various scenarios are used to assess its applicability.
Highlights
The emerging wireless technologies will enable new differentiated services and applications to support the needs of the 4th industrial revolution
As there are many small 5G cells under the larger coverage area of a 4G cell, we propose a smart MM algorithm based on NSA configuration with DC feature
We consider the situation where the coverage area is completely served by a 4G cell while the 5G coverage area varies and depends on the corresponding gNB profile, that is, density and footprint values
Summary
The emerging wireless technologies will enable new differentiated services and applications to support the needs of the 4th industrial revolution. The cell selection process takes into account several access network parameters such as BS capacity, channel state conditions (LOS: line-of-sight, NLOS: non-line-of-sight, and outage), number of attached users in the target BS, and most importantly signaling overhead which occurs during HO execution phase. Their work utilizes PMC to design mobile network controller and evaluates different MM schemes for target cell selection during HOs. The authors propose an efficient MM algorithm that enhances the network utilization and improves user perception by selecting better channel type. Our proposed framework considers a variety of parameters based on network topology and radio frequency to calculate the reward used in RAT selection It takes user velocity and 5G cell density into account to decide data split policy for various QoS requirements.
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