<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In order to reduce the power consumption, the Internet of Vehicles (IoV) system mostly adopts the modulation method of a single parameter such as phase. However, in scenarios that require transmitting a large amount of information, the single-information modulation method cannot meet the requirements of high data rates. To address this problem, the paper proposes a scheme of adding a small number of full-information channels containing both amplitude and phase information to form a nonlinear channel. The compressed sensing based algorithm is used to estimate the nonlinear channel. The information of channel is passed iteratively between the single-information channel and the full-information channel to obtain more accurate channel estimation. The paper also studies the influence of the mapping relationship between single-information channel and full-information channel, and the number of iterations on channel estimation accuracy. The results of the simulations show that the proposed scheme can increase the information transmission rate by 6 times at the cost of 2.5 times the power consumption.</p>
</abstract>

In order to reduce the power consumption, the Internet of Vehicles (IoV) system mostly adopts the modulation method of a single parameter such as phase. However, in scenarios that require transmitting a large amount of information, the single-information modulation method cannot meet the requirements of high data rates. To address this problem, the paper proposes a scheme of adding a small number of full-information channels containing both amplitude and phase information to form a nonlinear channel. The compressed sensing based algorithm is used to estimate the nonlinear channel. The information of channel is passed iteratively between the single-information channel and the full-information channel to obtain more accurate channel estimation. The paper also studies the influence of the mapping relationship between single-information channel and full-information channel, and the number of iterations on channel estimation accuracy. The results of the simulations show that the proposed scheme can increase the information transmission rate by 6 times at the cost of 2.5 times the power consumption.

Nonlinear channel estimation for Internet of Vehicles

Computer and Information Engineering Department

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Nonlinear channel estimation for Internet of Vehicles"}

In order to reduce the power consumption, the Internet of Vehicles (IoV) system mostly adopts the modulation method of a single parameter such as phase....

Nonlinear channel estimation for Internet of Vehicles

Publié en ligne: 10 nov. 2022

Pages: 2595 - 2604

Reçu: 03 mai 2022

Accepté: 30 août 2022

DOI: https://doi.org/10.2478/amns.2021.2.00304

Mots clés
IoV, Compressed sensing, Sparse reconstruction, Message Passing, Channel estimation

© 2023 Lv Zhiguo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Nonlinear channel estimation for Internet of Vehicles

Publié en ligne: 10 nov. 2022

Pages: 2595 - 2604

Reçu: 03 mai 2022

Accepté: 30 août 2022

DOI: https://doi.org/10.2478/amns.2021.2.00304

Mots clésIoV, Compressed sensing, Sparse reconstruction, Message Passing, Channel estimation

© 2023 Lv Zhiguo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Mots clés
IoV, Compressed sensing, Sparse reconstruction, Message Passing, Channel estimation