Tractable Mobility Model for Multi-Connectivity in 5G User-Centric Ultra-Dense Networks | Zendy

Hongtao Zhang | Zendy; Wanqing Huang | Zendy

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Tractable Mobility Model for Multi-Connectivity in 5G User-Centric Ultra-Dense Networks

Author(s) -

Hongtao Zhang,

Wanqing Huang

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2861915

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

With the network densification, frequent handovers may degrade mobility reliability, cause heavy signaling load thus blocking the improvement of network capacity. This paper aims at reducing cost in terms of handover in dense networks, deriving compact expressions of network performance metric, including handover probabilities as well as the mobility-aware downlink data rate, under a multi-connectivity mobility model in user-centric ultra-dense networks (UUDNs). Specifically, the nearest M access points (APs) in mobile user's vicinity serve the user for data transmission, while the best one among them is for control, which reduces handover probability and network overheads without a loss in the throughput performance gain. Based on the scheme, handover probabilities are derived for arbitrary movement trajectory in the UUDN, where the locations of APs are modeled as a homogeneous Poisson point process, and then is included in handover cost to derive the downlink rate for mobile users. It is shown that the handover probability in control-plane can considerably be decreased by at least 30% compared with the traditional single connectivity network. What is more, the downlink rate can be improved significantly by 2× compared with single connectivity.

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