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 language | English |
|---|---|
| Pages (from-to) | 1-12 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Vehicular Technology |
| Volume | 72 |
| Issue number | 8 |
| DOIs | |
| Publication status | Accepted/In press - 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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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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