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Outage Analysis Using Probabilistic Channel Model for Drone Assisted Multi-User Coded Cooperation System

  • Pankaj Kumar
  • , Sagnik Bhattacharyya
  • , Sam Darshi
  • , Sudhan Majhi
  • , Akram A. Almohammedi
  • , Samar Shailendra

    Research output: Contribution to journalArticlepeer-review

    Abstract

    This paper proposes a statistical-based channel modelling approach for a drone assisted multi-user coded cooperation (DA-MUCC) for evaluating the performance metrics of a next-generation wireless communication system. The proposed approach may find its applications in smart cities, disaster management and agriculture for building reliable communication links among ground users (GUs)/user equipments (UEs) over the scenarios where an infrastructure-based network (like a Base Station (BS)) is difficult to establish or disrupted. In such scenarios, an air-to-ground (A2G) channel is modelled based on the probabilistic approach of line-of-sight (LoS) and statistical independence of the links. The network performance of the proposed system model is evaluated by closed-form average outage probability and average rate over the Rayleigh and Rician fading channel models. The analytical performance is corroborated by Monte-Carlo simulations and also compared with the existing state-of-the-art approaches. Finally, we derive the probability density function (PDF) for signal-to-noise ratio (SNR) of relay link which is useful under the scenarios where the direct links among GUs are in the deep fade.

    Original languageEnglish
    Pages (from-to)1-12
    Number of pages12
    JournalIEEE Transactions on Vehicular Technology
    Volume72
    Issue number8
    DOIs
    Publication statusAccepted/In press - 2023

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 11 - Sustainable Cities and Communities
      SDG 11 Sustainable Cities and Communities

    All Science Journal Classification (ASJC) codes

    • Automotive Engineering
    • Aerospace Engineering
    • Electrical and Electronic Engineering
    • Applied Mathematics

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