Management of Wireless Communication Systems Using Artificial Intelligence-Based Software Defined Radio
Open accessAbstract
The wireless communication system was investigated by novel methods, which produce an optimized data link, especially the software-based methods. Software-Defined Radio (SDR) is a common method for developing and implementing wireless communication protocols. In this paper, SDR and artificial intelligence (AI) are used to design a self-management communication system with variable node locations. Three affected parameters for the wireless signal are considered: channel frequency, bandwidth, and modulation type. On one hand, SDR collects and analyzes the signal components while on the other hand, AI processes the situation in real-time sequence after detecting unwanted data during the monitoring stage. The decision was integrated into the system by AI with respect to the instantaneous data read then passed to the communication nodes to take its correct location. The connectivity ratio and coverage area are optimized nearly double by the proposed method, which means the variable node location, according to the peak time, increases the attached subscriber by a while ratio
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IoST can also find application in deep space exploration through interplanetary data relaying, sensing and monitoring of asteroids, Mars, and Moon.
“Notwithstanding the many use cases for IoST that focus on on-Earth or near-Earth applications, it is worth stating that IoST can also can find application in deep space exploration through interplanetary data relaying, sensing and monitoring of asteroids, Mars, and Moon [260, 263].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [263]
Currently, the utmost goal of IoST is to enable global connectivity beyond planet earth and provide sensing capabilities at a low cost.
“Currently, the utmost goal of IoST is to enable global connectivity beyond planet earth and provide sensing capabilities at a low cost [263].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [263]
Cites
NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey
Akyildiz, I. F., Lee, W.-Y., Vuran, M. C., & Mohanty, S. (2006) · Computer Networks · doi:10.1016/j.comnet.2006.05.001 · Cited by 6,356 · see citing works
Piccinini, G. (2004) · Synthese · doi:10.1023/b:synt.0000043018.52445.3e · Cited by 215 · see citing works
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Applications and Challenges of Artificial Intelligence in Space Missions
Oche, P. A., Ewa, G. A., & Ibekwe, N. (2024) · IEEE Access · doi:10.1109/access.2021.3132500 · Cited by 68 · see citing works
“Over the last couple of years research interest in the use of AI and SDR to manage networks and communication systems has gained momentum [262].”
Background
- Authors
- Bargarai, F. A. M., Abdulazeez, A. M., Tiryaki, V. M., & Zeebaree, D. Q.
- Affiliations
- Duhok Polytechnic University (IQ)
- Siirt Üniversitesi (TR)
- Venue
- International Journal of Interactive Mobile Technologies (iJIM)
- Published
- 2020-08-14
- Volume
- 14
- Issue
- 13
- Pages
- 107
- ISSN
- 1865-7923 (ISSN-L)
- OpenAlex
- W3049462790
- Cited by
- 49
- References
- 2
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 15 · 2023: 11 · 2022: 3 · 2021: 15 · 2020: 1
- FWCI
- 3.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- International Journal of Interactive Mobile Technologies (iJIM) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Cognitive Radio Networks and Spectrum Sensing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Network Optimization
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Keywords
- software-defined radio, artificial intelligence, wireless communication, bandwidth allocation, real-time signal monitoring
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