Link Level Performance Comparison of C-V2X and ITS-G5 for Vehicular Channel Models

Sattiraju, Raja; Wang, Donglin; Weinand, Andreas; Schotten, Hans D.

doi:10.1109/vtc2020-spring48590.2020.9129366

Cited by 21 publications

(11 citation statements)

References 10 publications

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“…), which will also create an unfair situation for customers, as Rel-15 cars will have more advanced features as compared to Rel-14 cars [7]. Generally, we can say that LTE (especially Rel-14)) is not ready yet as compared to ITS-G5 as the testing has not been done according to the required standards [38].…”

Section: Readinessmentioning

confidence: 99%

“…Similarly, 5G NR technology is not backward compatible with LTE Rel-15 & Rel-14. Therefore, LTE implementation will always be equipped with previous versions in case it relies on services from previous releases, e.g., basic safety messages [7,38].…”

Section: Compatibilitymentioning

confidence: 99%

“…ITS-G5 provides high mobility even for long distances by using a turbo-codec compared to LTE, which does not provide the same performance at high speed even with advanced block-based codecs (like LDPC) as these codecs cannot be decoded per symbol [38].…”

Section: High Mobility Environmentmentioning

confidence: 99%

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Vehicular Wireless Communication Standards

Uzair

2022

Int. j. electr. comput. eng. syst. (Online)

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Autonomous vehicles (AVs) are the future of mobility. Safe and reliable AVs are required for widespread adoption by a community which is only possible if these AVs can communicate with each other & with other entities in a highly efficient way. AVs require ultra-reliable communications for safety-critical applications to ensure safe driving. Existing vehicular communication standards, i.e., IEEE 802.11p (DSRC), ITS-G5, & LTE, etc., do not meet the requirements of high throughput, ultra-high reliability, and ultra-low latency along with other issues. To address these challenges, IEEE 802.11bd & 5G NR-V2X standards provide more efficient and reliable communication, however, these standards are in the developing stage. Existing literature generally discusses the features of these standards only and does not discuss the drawbacks. Similarly, existing literature does not discuss the comparison between these standards or discusses a comparison between any two standards only. However, this work comprehensively describes different issues/challenges faced by these standards. This work also comprehensively provides a comparison among these standards along with their salient features. The work also describes spectrum management issues comprehensively, i.e., interoperability issues, co-existence with Wi-Fi, etc. The work also describes different other issues comprehensively along with recommendations. The work describes that 802.11bd and 5G NR are the two potential future standards for efficient vehicle communications; however, these standards must be able to provide backward compatibility, interoperability, and co-existence with current and previous standards.

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Section: Readinessmentioning

confidence: 99%

Section: Compatibilitymentioning

confidence: 99%

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Vehicular Wireless Communication Standards

Uzair

2022

Int. j. electr. comput. eng. syst. (Online)

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“…The 0th and the central 11 subcarriers are null. Those with indices 7, 10, 44 and 58 are occupied by pilot symbols, and the remaining 48 are used for carrying data [ 25 ]. The OFDM symbol lasts 8 µs and the subcarrier spacing is 156.25 kHz, leading to a raw bandwidth of 10 MHz.…”

Section: Signal Modelmentioning

confidence: 99%

V2X Wireless Technology Identification Using Time–Frequency Analysis and Random Forest Classifier

Skiribou

Elbahhar

2021

Sensors

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Signal identification is of great interest for various applications such as spectrum sharing and interference management. A typical signal identification system can be divided into two steps. A feature vector is first extracted from the received signal, then a decision is made by a classification algorithm according to its observed values. Some existing techniques show good performance but they are either sensitive to noise level or have high computational complexity. In this paper, a machine learning algorithm is proposed for the identification of vehicular communication signals. The feature vector is made up of Instantaneous Frequency (IF) resulting from time–frequency (TF) analysis. Its dimension is then reduced using the Singular Value Decomposition (SVD) technique, before being fed into a Random Forest classifier. Simulation results show the relevance and the low complexity of IF features compared to existing cyclostationarity-based ones. Furthermore, we found that the same accuracy can be maintained regardless of the noise level. The proposed framework thus provides a more accurate, robust and less complex V2X signal identification system.

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“…However, in order to be considered as an IMT-2020 technology, its performance needs to be evaluated against the requirements defined in IMT-2020. In the literature, link-level performance of new technologies is usually evaluated by using standard channel models [9]. IMT-2020 has already provided different channel models to evaluate the candidate technologies in [10].…”

Section: Background and Related Workmentioning

confidence: 99%

Link-Level Performance Evaluation of IMT-2020 Candidate Technology: DECT-2020 New Radio

Penner,

Nabeel,

Peissig

2021

Preprint

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The ETSI has recently introduced the DECT-2020 New Radio (NR) as an IMT-2020 candidate technology for the mMTC and URLLC use cases. To consider DECT-2020 NR as an IMT-2020 technology, the ITU-R has determined different independent evaluation groups to assess its performance against the IMT-2020 requirements. These independent evaluation groups are now in process of investigating the DECT-2020 NR. In order to successfully assess a technology, one important aspect is to fully understand the underlying physical layer and its performance in different environments. Therefore, in this paper, we focus on the physical layer of DECT-2020 NR and investigate its link-level performance with standard channel models provided by the ITU-R for evaluation. We perform extensive simulations to analyze the performance of DECT-2020 NR for both URLLC and mMTC use cases. The results presented in this work are beneficial for the independent evaluation groups and researchers as these results can help calibrating their physical layer performance curves. These results can also be used directly for future system-level evaluations of DECT-2020 NR.

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Link Level Performance Comparison of C-V2X and ITS-G5 for Vehicular Channel Models

Cited by 21 publications

References 10 publications

Vehicular Wireless Communication Standards

Vehicular Wireless Communication Standards

V2X Wireless Technology Identification Using Time–Frequency Analysis and Random Forest Classifier

Link-Level Performance Evaluation of IMT-2020 Candidate Technology: DECT-2020 New Radio

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