Multiple sequential constraint removal ...
Document type :
Communication dans un congrès avec actes
Title :
Multiple sequential constraint removal algorithm for channel estimation in vehicular environment
Author(s) :
Ribouh, Soheyb [Auteur]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
El Hillali, Yassin [Auteur]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Rivenq, Atika [Auteur]
INSA Institut National des Sciences Appliquées Hauts-de-France [INSA Hauts-De-France]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
El Hillali, Yassin [Auteur]

COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Rivenq, Atika [Auteur]

INSA Institut National des Sciences Appliquées Hauts-de-France [INSA Hauts-De-France]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Conference title :
International Symposium on Networks, Computers and Communications, ISNCC 2020
City :
Montreal
Country :
Canada
Start date of the conference :
2020-10-20
Publisher :
Institute of Electrical and Electronics Engineers Inc.
Publication date :
2020
English keyword(s) :
V2X communications
Receivers
Channel estimation
Doubly-selective-channel
MSCR Algorithm
Receivers
Channel estimation
Doubly-selective-channel
MSCR Algorithm
HAL domain(s) :
Sciences de l'ingénieur [physics]
Informatique [cs]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Réseaux et télécommunications [cs.NI]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Sciences de l'ingénieur [physics]/Electronique
Informatique [cs]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Réseaux et télécommunications [cs.NI]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Sciences de l'ingénieur [physics]/Electronique
English abstract : [en]
Since the vehicular environment is highly mobile, the transmitted messages are affected by the wireless channel effect. This makes channel estimation one of the important tasks in Vehicle-To-Everything (V2X) communications. ...
Show more >Since the vehicular environment is highly mobile, the transmitted messages are affected by the wireless channel effect. This makes channel estimation one of the important tasks in Vehicle-To-Everything (V2X) communications. In this paper, we propose a novel Multiple Sequential Constraint Removal (MSCR) algorithm of channel estimation, dedicated to V2X communications. This method is performed on a vehicular doubly selective channel, where the communication system is based on the Orthogonal Frequency Division Multiplexing (OFDM) waveform, with a high order modulation (64-QAM). The proposed approach is compared to state-of-the-art Least square (LS), minimum mean square error (MMSE) estimators and the iterative Sequential Constraint Removal (SCR) algorithms. It shows that it achieves better performance, where we can get a small symbol error rate (SER) on highly mobile scenarios (Highway with non-line of the sight), with a latency time that meets with the V2X communication requirements. © 2020 IEEE.Show less >
Show more >Since the vehicular environment is highly mobile, the transmitted messages are affected by the wireless channel effect. This makes channel estimation one of the important tasks in Vehicle-To-Everything (V2X) communications. In this paper, we propose a novel Multiple Sequential Constraint Removal (MSCR) algorithm of channel estimation, dedicated to V2X communications. This method is performed on a vehicular doubly selective channel, where the communication system is based on the Orthogonal Frequency Division Multiplexing (OFDM) waveform, with a high order modulation (64-QAM). The proposed approach is compared to state-of-the-art Least square (LS), minimum mean square error (MMSE) estimators and the iterative Sequential Constraint Removal (SCR) algorithms. It shows that it achieves better performance, where we can get a small symbol error rate (SER) on highly mobile scenarios (Highway with non-line of the sight), with a latency time that meets with the V2X communication requirements. © 2020 IEEE.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Source :