21,351 research outputs found

    Group Mobility Detection and User Connectivity Models for Evaluation of Mobile Network Functions

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    Group mobility in mobile networks is responsible for dynamic changes in user accesses to base stations, which eventually lead to degradation of network quality of service (QoS). In particular, the rapid movement of a dense group of users intensively accessing the network, such as passengers on a train passing through a densely populated area, significantly affects the perceived network QoS. For better design and operation of mobile network facilities and functions in response to this issue, monitoring group mobility and modeling the access patterns in group mobility scenarios are essential. In this paper, we focus on fast and dense group mobility and mobile network signaling data (control-plane data), which contains information related to mobility and connectivity. Firstly, we develop a lightweight method of group mobility detection to extract train passengers from all users\u27 signaling data without relying on precise location information about users, e.g., based on GPS. Secondly, based on the same signaling data and the results obtained by the detection method, we build connected/idle duration models for train users and non-train users. Finally, we leverage these models in mobile network simulations to assess the effectiveness of a dynamic base station switching/orientation scheme to mitigate QoS degradation with low power consumption in a group mobility scenario. The obtained models reveal that train users consume 3.5 times more resources than non-train users, which proves that group mobility has a significant effect on mobile networks. The simulation results show that the dynamic scheme of base station improves users\u27 perceived throughput, latency and jitter with small amount of additional power consumption in case of a moderate number of train users, but its ineffectiveness with larger number of train users is also shown. This would suggest that group mobility detection and the obtained connection/idle duration models based solely on control-plane data analytics are usable and useful for the development of mobility-aware functions in base stations

    MoMo: a group mobility model for future generation mobile wireless networks

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    Existing group mobility models were not designed to meet the requirements for accurate simulation of current and future short distance wireless networks scenarios, that need, in particular, accurate, up-to-date informa- tion on the position of each node in the network, combined with a simple and flexible approach to group mobility modeling. A new model for group mobility in wireless networks, named MoMo, is proposed in this paper, based on the combination of a memory-based individual mobility model with a flexible group behavior model. MoMo is capable of accurately describing all mobility scenarios, from individual mobility, in which nodes move inde- pendently one from the other, to tight group mobility, where mobility patterns of different nodes are strictly correlated. A new set of intrinsic properties for a mobility model is proposed and adopted in the analysis and comparison of MoMo with existing models. Next, MoMo is compared with existing group mobility models in a typical 5G network scenario, in which a set of mobile nodes cooperate in the realization of a distributed MIMO link. Results show that MoMo leads to accurate, robust and flexible modeling of mobility of groups of nodes in discrete event simulators, making it suitable for the performance evaluation of networking protocols and resource allocation algorithms in the wide range of network scenarios expected to characterize 5G networks.Comment: 25 pages, 17 figure

    An Efficient Uplink Multi-Connectivity Scheme for 5G mmWave Control Plane Applications

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    The millimeter wave (mmWave) frequencies offer the potential of orders of magnitude increases in capacity for next-generation cellular systems. However, links in mmWave networks are susceptible to blockage and may suffer from rapid variations in quality. Connectivity to multiple cells - at mmWave and/or traditional frequencies - is considered essential for robust communication. One of the challenges in supporting multi-connectivity in mmWaves is the requirement for the network to track the direction of each link in addition to its power and timing. To address this challenge, we implement a novel uplink measurement system that, with the joint help of a local coordinator operating in the legacy band, guarantees continuous monitoring of the channel propagation conditions and allows for the design of efficient control plane applications, including handover, beam tracking and initial access. We show that an uplink-based multi-connectivity approach enables less consuming, better performing, faster and more stable cell selection and scheduling decisions with respect to a traditional downlink-based standalone scheme. Moreover, we argue that the presented framework guarantees (i) efficient tracking of the user in the presence of the channel dynamics expected at mmWaves, and (ii) fast reaction to situations in which the primary propagation path is blocked or not available.Comment: Submitted for publication in IEEE Transactions on Wireless Communications (TWC
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