Kumar, PankajBhattacharyya, SagnikDarshi, SamMajhi, SudhanAlmohammedi, Akram A.Shailendra, Samar2024-09-292024-09-2920230018-95451939-9359https://doi.org/10.1109/TVT.2023.3257229https://hdl.handle.net/20.500.14619/6183This 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.eninfo:eu-repo/semantics/closedAccessDronesRician channelsChannel modelsRelaysDownlinkUplinkAutonomous aerial vehiclesMulti-user cooperationDroneNetwork codingNetwork coding noiseRician channelRayleigh channelStatistical channel modelOutage probabilityRateArticle10.1109/TVT.2023.32572292-s2.0-85151544413102858Q11027372WOS:001153701000047Q1