Computational Experiments and Comparative Analysis of Signal Detection Algorithms in Vehicular Ad Hoc Networks
In the era of rapid development of vehicular ad hoc networks (VANETs), ensuring the reliability and security of vehicle-to-vehicle communication has become a top priority. This paper comprehensively analyzes the performance of various signal detection algorithms in different scenarios. To intelligen...
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| Vydané v: | IEEE journal of radio frequency identification (Online) Ročník 8; s. 402 - 411 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2469-7281, 2469-729X |
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| Abstract | In the era of rapid development of vehicular ad hoc networks (VANETs), ensuring the reliability and security of vehicle-to-vehicle communication has become a top priority. This paper comprehensively analyzes the performance of various signal detection algorithms in different scenarios. To intelligently choose different signal detection algorithms in the context of VANETs, the study covers diverse scenarios such as urban environments, rural areas, highways, parking lots, and mountainous regions, aiming to capture subtle variations in the performance of different signal detection algorithms across these scenarios. The paper employs strict performance metrics, such as bit error rate and algorithmic complexity, to quantify and compare the performance of different signal detection algorithms. The focus is on the role of signal detection algorithms in achieving parallel intelligence in VANETs, including the simultaneous processing of signals from multiple vehicles to enhance overall network efficiency and reliability. This research holds significance by providing insights into the strengths and limitations of signal detection algorithms in VANETs, guiding their development for efficient and accurate performance, thereby contributing to academic understanding and informing decision-making in the automotive industry and intelligent transportation systems. |
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| AbstractList | In the era of rapid development of vehicular ad hoc networks (VANETs), ensuring the reliability and security of vehicle-to-vehicle communication has become a top priority. This paper comprehensively analyzes the performance of various signal detection algorithms in different scenarios. To intelligently choose different signal detection algorithms in the context of VANETs, the study covers diverse scenarios such as urban environments, rural areas, highways, parking lots, and mountainous regions, aiming to capture subtle variations in the performance of different signal detection algorithms across these scenarios. The paper employs strict performance metrics, such as bit error rate and algorithmic complexity, to quantify and compare the performance of different signal detection algorithms. The focus is on the role of signal detection algorithms in achieving parallel intelligence in VANETs, including the simultaneous processing of signals from multiple vehicles to enhance overall network efficiency and reliability. This research holds significance by providing insights into the strengths and limitations of signal detection algorithms in VANETs, guiding their development for efficient and accurate performance, thereby contributing to academic understanding and informing decision-making in the automotive industry and intelligent transportation systems. |
| Author | Xie, Yupei Hao, Conghui Li, Yi Han, Shuangshuang |
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| SubjectTerms | Algorithms Automobile industry Bit error rate Intelligent transportation systems Interference cancellation Mobile ad hoc networks Mountainous areas Nakagami distribution Network reliability parallel intelligence Parallel processing Performance measurement Rician channels Rural environments Scenario generation scenario-based channels Signal detection signal detection algorithms Transportation Transportation networks Urban environments Vehicular ad hoc networks |
| Title | Computational Experiments and Comparative Analysis of Signal Detection Algorithms in Vehicular Ad Hoc Networks |
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