Linear state estimation via 5G C-RAN cellular networks using Gaussian belief propagation

Cosovic, Mirsad and Vukobratovic, Dejan and Stankovic, Vladimir (2018) Linear state estimation via 5G C-RAN cellular networks using Gaussian belief propagation. In: IEEE Wireless Communications and Networking Conference, 2018-04-15 - 2018-04-18.

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Abstract

Machine-type communications and large-scale information processing architectures are among key (r)evolutionary enhancements of emerging fifth-generation (5G) mobile cellular networks. Massive data acquisition and processing will make 5G network an ideal platform for large-scale system monitoring and control with applications in future smart transportation, connected industry, power grids, etc. In this work, we investigate a capability of such a 5G network architecture to provide the state estimate of an underlying linear system from the input obtained via large-scale deployment of measurement devices. Assuming that the measurements are communicated via densely deployed cloud radio access network (C-RAN), we formulate and solve the problem of estimating the system state from the set of signals collected at C-RAN base stations. Our solution, based on the Gaussian Belief-Propagation (GBP) framework, allows for large-scale and distributed deployment within the emerging 5G information processing architectures. The presented numerical study demonstrates the accuracy, convergence behavior and scalability of the proposed GBP-based solution to the large-scale state estimation problem.

  • Item type:Conference or Workshop Item(Paper)
    ID code:62992
    Dates:
    Date
    Event
    15 April 2018
    Published
    15 December 2017
    Accepted
    Notes:(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:23 Jan 2018 12:21
    Last modified:09 Apr 2024 06:26
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/62992
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