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Interference Mitigation based on NOMA for Scheduling Algorithm in V2X Environments
Abstract
The Intelligent Transport System (ITS) is a basic application scenario in next-generation wireless networks, which require ultra-high throughput and ultra-low latency. More recently, non-orthogonal multiple access (NOMA) has been seen as a promising technique to meet the growing demand for data traffic for future 5G systems. The NOMA technique makes it possible to share the same resource by several issuers. However, the sharing of resources between a set of users, causes an interference problem. As a result, interference mitigation (IM) is becoming a more important phenomenon in NOMA-based vehicle networks. This work presents a new algorithm called SAVCN-IM (Scheduling Algorithm for V2X Communication based on NOMA with Interference Mitigation), for the 5G network. The proposed algorithm reduces interference to improve network performance in terms of throughput and error rates. In fact, the SAVCN-IM assigns the available resource blocks (RBs) in order to maximize throughput taking into account the value of SINR between transmitters and receivers. It also maximizes the number of V2X users served and minimizes the bit error rate. Simulation results indicate promising performance for SAVCN-IM.
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A mobile cloud and edge computing delay prediction framework is proposed to improve real-time communication, and frameworks such as Ref. and Ref. are proposed to minimize mutual interference among V2X communication.
“A mobile cloud and edge computing delay prediction framework [38] is proposed to improve real-time communication, and frameworks such as Ref. [90] and Ref. [91] are proposed to minimize mutual interference among V2X communication.”
From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [91]
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Research works printed but not linked: 18
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Cited by
Sorted by citations
Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy
Zhang, X., Li, J., Zhou, J., Zhang, S., Wang, J., Yuan, Y., Liu, J., & Li, J. (2025) · Automotive Innovation · doi:10.1007/s42154-024-00310-2 · Cited by 103
Metadata
- Authors
- Rigane, E. B., Marouane, H., Trabelsi, A., & Zarai, F.
- Affiliations
- University of Sfax (TN)
- Venue
- 2020 International Wireless Communications and Mobile Computing (IWCMC)
- Publisher
- IEEE
- Published
- 2020-06
- Pages
- 1952-1957
- OpenAlex
- W3045612554
- Cited by
- 7
- References
- 0
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 2 · 2021: 1
- FWCI
- 1.05
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Wireless Communications and Mobile Computing Conference (IWCMC) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- non-orthogonal multiple access, interference mitigation, vehicle-to-everything communication, scheduling algorithms, resource block allocation, 5G, intelligent transportation systems, SINR, throughput maximization, bit error rate, vehicular networks
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