Outage probability analysis of uplink heterogeneous non-terrestrial networks: a novel stochastic geometry model
Outage probability analysis of uplink heterogeneous non-terrestrial networks: a novel stochastic geometry model
In harsh environments such as mountainous terrain, dense vegetation areas, or urban landscapes, a single type of unmanned aerial vehicles (UAVs) may encounter challenges like flight restrictions, difficulty in task execution, or increased risk. Therefore, employing multiple types of UAVs, along with satellite assistance, to collaborate becomes essential in such scenarios. In this context, we present a stochastic geometry based approach for modeling the heterogeneous non-terrestrial networks (NTNs) by using the classical binomial point process and introducing a novel point process, called Matern hard-core cluster process (MHCCP). Our MHCCP possesses both the exclusivity and the clustering properties, thus it can better model the aircraft group composed of multiple clusters. Then, we derive closed-form expressions of the outage probability (OP) for the uplink (aerial to-satellite) of heterogeneous NTNs. Unlike existing studies, our analysis relies on a more advanced system configuration, where the integration of beamforming and frequency division multiple access, and the shadowed-Rician (SR) fading model for interference power, are considered. The accuracy of our theoretical derivation is confirmed by Monte Carlo simulations. Our research offers fundamental insights into the system-level performance optimization of NTNs.
Dong, Wen-Yu
c0247ccb-4b0b-4ccb-8ec6-b01aaed6cb70
Yang, Shaoshi
23650ec4-bcc8-4a2c-b1e7-a30893f52e52
Lin, Wei
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Zhao, Wei
4f5ab09f-7c2e-41b0-9004-212eacd92ed7
Gui, Jia-Xing
4aae2e46-62e8-4337-a69b-cf6deae9fd70
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
8 December 2024
Dong, Wen-Yu
c0247ccb-4b0b-4ccb-8ec6-b01aaed6cb70
Yang, Shaoshi
23650ec4-bcc8-4a2c-b1e7-a30893f52e52
Lin, Wei
d7b04e93-7fa4-4442-b6d6-622099d52f27
Zhao, Wei
4f5ab09f-7c2e-41b0-9004-212eacd92ed7
Gui, Jia-Xing
4aae2e46-62e8-4337-a69b-cf6deae9fd70
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Dong, Wen-Yu, Yang, Shaoshi, Lin, Wei, Zhao, Wei, Gui, Jia-Xing and Chen, Sheng
(2024)
Outage probability analysis of uplink heterogeneous non-terrestrial networks: a novel stochastic geometry model.
In Proceedings of IEEE Global Communications Conference (GLOBECOM 2024).
IEEE.
6 pp
.
(doi:10.1109/GLOBECOM52923.2024.10901355).
Record type:
Conference or Workshop Item
(Paper)
Abstract
In harsh environments such as mountainous terrain, dense vegetation areas, or urban landscapes, a single type of unmanned aerial vehicles (UAVs) may encounter challenges like flight restrictions, difficulty in task execution, or increased risk. Therefore, employing multiple types of UAVs, along with satellite assistance, to collaborate becomes essential in such scenarios. In this context, we present a stochastic geometry based approach for modeling the heterogeneous non-terrestrial networks (NTNs) by using the classical binomial point process and introducing a novel point process, called Matern hard-core cluster process (MHCCP). Our MHCCP possesses both the exclusivity and the clustering properties, thus it can better model the aircraft group composed of multiple clusters. Then, we derive closed-form expressions of the outage probability (OP) for the uplink (aerial to-satellite) of heterogeneous NTNs. Unlike existing studies, our analysis relies on a more advanced system configuration, where the integration of beamforming and frequency division multiple access, and the shadowed-Rician (SR) fading model for interference power, are considered. The accuracy of our theoretical derivation is confirmed by Monte Carlo simulations. Our research offers fundamental insights into the system-level performance optimization of NTNs.
Text
globcom2024-p2
- Accepted Manuscript
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Published date: 8 December 2024
Venue - Dates:
IEEE Global Communications Conference (GLOBECOM 2024), , Cape Town, South Africa, 2024-12-08 - 2024-12-12
Identifiers
Local EPrints ID: 496997
URI: http://eprints.soton.ac.uk/id/eprint/496997
PURE UUID: fac70021-f3d5-4502-a5ee-e9e6ba458035
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Date deposited: 09 Jan 2025 18:00
Last modified: 25 Apr 2025 16:43
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Contributors
Author:
Wen-Yu Dong
Author:
Shaoshi Yang
Author:
Wei Lin
Author:
Wei Zhao
Author:
Jia-Xing Gui
Author:
Sheng Chen
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